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  Answering Machine (disambiguation)
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  Hell No

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  Answering Machine (disambiguation)
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• Answering machine
• Answering machine (disambiguation)
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Answering machine

The answering machine, answerphone or message machine, also known as the telephone answering machine (or TAM) in the UK and some Commonwealth countries, ansaphone or ansafone (from a trade name), or telephone answering device (TAD) is a device for answering telephones and recording callers' messages.

Unlike voicemail, which can be a centralized or networked system that performs a similar function, an answering machine must be set up in the user's premises alongside — or incorporated within — the user's telephone.

History

The tape answering machine records and replays sound using a technique originally invented in 1898 by Valdemar Poulsen which was the first practical device used for recording telephone conversations. Poulsen's device, known as a telegraphone or 'wire recorder', laid the foundation for the invention of the answering machines used today (though it was also used to record dictation and even music.) The creation of the first practical automatic answering device for telephones is in dispute. Clarence Hickman worked for Bell Laboratories from 1930 where he developed methods for the magnetic recording and working on the recognition of speech patterns and electromechanical switching systems. In 1934 he developed a tape-based answering machine which the phone company AT&T, as the owner of Bell Laboratories, kept under wraps for years for fears that an answering machine would result in fewer telephone calls. Many claim it was William Muller in 1935, but it could have been created already in 1931 by William Schergens whose device used phonographic cylinders.Ludwig Blattner promoted a telephone answering machine in 1929 based on his Blattnerphone magnetic recording technology.

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This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Answering_machine

Answering machine (disambiguation)

An answering machine is a device for automatically answering telephone calls and recording messages left by callers.

Answering Machine may also refer to:

question answering machine.

The Answering Machine, a British indie band from Manchester

The Answer Machine?, eighth full-length album by British folk metal band Skyclad

Answering Machine Music, a 1999 album by Casiotone for the Painfully Alone

"Answering Machine", a song by The Replacements from the 1984 album Let It Be

"The Answering Machine", a song by Marillion from the 1998 album Radiation

"Answering Machine", a song by Cherry Poppin' Daddies from the 1990 album Ferociously Stoned

"Answering Machine", a song by Rupert Holmes

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This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Answering_machine_(disambiguation)

Hell No

Hell No may refer to:

"wikt:hell no", a negative exclamation shouted when a less than pleasing event occurs, can be abbreviated: HN!

Music

"Hell No!", a 2005 single by Australian pop singer Ricki Lee Coulter

"Hell No (Leave Home)", a 2007 single by American R&B singer Monica

"Hell No", a song by The Hives 2007

"Hell No", a bonus track by The Hives on The Black and White Album, 2007

Sport

Team Hell No, a WWE Tag Team formed of Kane and Daniel Bryan.

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This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Hell_No

Hell No!

"Hell No!" is the debut single by Australian recording artist Ricki-Lee Coulter. It was released as a CD single in June 2005, as the lead single from her self-titled debut album, Ricki-Lee. "Hell No!" debuted and peaked at number five on the ARIA Singles Chart and was certified gold by the Australian Recording Industry Association for shipments of 35,000 copies. The music video for the song was directed by Bart Borghesi.

Background and reception

"Hell No!" was written by Audius Mtawarira, Andy Love and Cheryline Lim, and produced by Mtawarira. It was released as a CD single in June 2005, as the lead single from Coulter's self-titled debut album, Ricki-Lee. Lyrically, the song is about Coulter being frustrated with life. According to The Hot Hits, "Hell No!" has the "in your face yet tongue in cheek attitude" and wrote that "the hot grooved, up-tempo track is perhaps not what many people expected from the 19 year old, 2004 Idol favourite".The Age noted that "Hell No!" has "a funky street feel to it". Matthew Chisling of Allmusic wrote "Coulter's versatile voice booms proudly" on the song. "Hell No!" debuted and peaked at number five on the ARIA Singles Chart on 20 June 2005 and spent three consecutive weeks in the top ten. The song was certified gold by the Australian Recording Industry Association for shipments of 35,000 copies.

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This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Hell_No!

Hell No (Leave Home)

"Hell No (Leave Home)" is a song by American singer Monica. It was written by Bryan Michael Cox, Sean Garrett, and Carl Mitchell and co-produced by Cox and Garrett, and features guest vocals by rapper Twista for her fourth studio album, The Makings of Me (2006). The song was released as the album's fourth and final single on May 14, 2007 (see 2007 in music) in the United States during the second quarter of 2007 (see 2007 in music). With a lack of promotion from the record label, the single failed to chart on the U.S. Billboard Hot 100. It reached a peak position of number 114 on the U.S. Billboard Hot R&B/Hip-Hop Songs chart.

Formats and tracklistings

These are the formats and track listings of major single-releases of "Hell No (Leave Home)."

Promotional CD single

"Hell No (Leave Home)" (Radio Edit) - 4:36

"Hell No (Leave Home)" (Radio Edit Without Rap) - 3:19

"Hell No (Leave Home)" (Instrumental) - 4:49

"Hell No (Leave Home)" (Call out Hook) - 0:17

Charts

References

External links

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This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Hell_No_(Leave_Home)

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11:18

GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge (Research Paper Walkthrough)

• Order: Reorder
• Duration: 11:18
• Uploaded Date: 07 Apr 2021
• views: 2095

#bert #wsd #wordnet This research uses BERT for Word Sense Disambiguation use case in NLP by modeling the entire problem as sentence classification task using t...

#bert #wsd #wordnet This research uses BERT for Word Sense Disambiguation use case in NLP by modeling the entire problem as sentence classification task using the Gloss knowledge. They show state-of-art results on benchmark datasets. ⏩ Abstract: Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a particular context. Traditional supervised methods rarely take into consideration the lexical resources like WordNet, which are widely utilized in knowledge-based methods. Recent studies have shown the effectiveness of incorporating gloss (sense definition) into neural networks for WSD. However, compared with traditional word expert supervised methods, they have not achieved much improvement. In this paper, we focus on how to better leverage gloss knowledge in a supervised neural WSD system. We construct context-gloss pairs and propose three BERT-based models for WSD. We fine-tune the pre-trained BERT model on SemCor3.0 training corpus and the experimental results on several English all-words WSD benchmark datasets show that our approach outperforms the state-of-the-art systems. Please feel free to share out the content and subscribe to my channel :) ⏩ Subscribe - https://youtube.com/channel/UCoz8NrwgL7U9535VNc0mRPA?sub_confirmation=1 ⏩ OUTLINE: 0:00 - Abstract 01:46 - Task Definition 02:11 - Data Collection approach 02:30 - WordNet Overview 03:35 - Sentence construction method table overview 05:27 - BERT(Token-CLS) 06:41 - GlossBERT 07:52 - Context-Gloss Pair with Weak Supervision 08:55 - GlossBERT(Token-CLS) 09:20 - GlossBERT(Sent-CLS) 09:44 - GlossBERT(Sent-CLS-WS) 10:09 - Results ⏩ Paper Title: GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge ⏩ Paper: https://arxiv.org/abs/1908.07245v4 ⏩ Code: https://github.com/HSLCY/GlossBERT ⏩ Author: Luyao Huang, Chi Sun, Xipeng Qiu, Xuanjing Huang ⏩ Organisation: Fudan University ⏩ IMPORTANT LINKS Full Playlist on BERT usecases in NLP: https://www.youtube.com/watch?v=kC5kP1dPAzc&list=PLsAqq9lZFOtV8jYq3JlkqPQUN5QxcWq0f Full Playlist on Text Data Augmentation Techniques: https://www.youtube.com/watch?v=9O9scQb4sNo&list=PLsAqq9lZFOtUg63g_95OuV-R2GhV1UiIZ Full Playlist on Text Summarization: https://www.youtube.com/watch?v=kC5kP1dPAzc&list=PLsAqq9lZFOtV8jYq3JlkqPQUN5QxcWq0f Full Playlist on Machine Learning with Graphs: https://www.youtube.com/watch?v=-uJL_ANy1jc&list=PLsAqq9lZFOtU7tT6mDXX_fhv1R1-jGiYf Full Playlist on Evaluating NLG Systems: https://www.youtube.com/watch?v=-CIlz-5um7U&list=PLsAqq9lZFOtXlzg5RNyV00ueE89PwnCbu ********************************************* If you want to support me financially which totally optional and voluntary :) ❤️ You can consider buying me chai ( because i don't drink coffee :) ) at https://www.buymeacoffee.com/TechvizCoffee ********************************************* ⏩ Youtube - https://www.youtube.com/c/TechVizTheDataScienceGuy ⏩ Blog - https://prakhartechviz.blogspot.com ⏩ LinkedIn - https://linkedin.com/in/prakhar21 ⏩ Medium - https://medium.com/@prakhar.mishra ⏩ GitHub - https://github.com/prakhar21 ⏩ Twitter - https://twitter.com/rattller ********************************************* Please feel free to share out the content and subscribe to my channel :) ⏩ Subscribe - https://youtube.com/channel/UCoz8NrwgL7U9535VNc0mRPA?sub_confirmation=1 Tools I use for making videos :) ⏩ iPad - https://tinyurl.com/y39p6pwc ⏩ Apple Pencil - https://tinyurl.com/y5rk8txn ⏩ GoodNotes - https://tinyurl.com/y627cfsa #techviz #datascienceguy #ai #researchpaper #naturallanguageprocessing #bart

https://wn.com/Glossbert_Bert_For_Word_Sense_Disambiguation_With_Gloss_Knowledge_(Research_Paper_Walkthrough)

#bert #wsd #wordnet This research uses BERT for Word Sense Disambiguation use case in NLP by modeling the entire problem as sentence classification task using the Gloss knowledge. They show state-of-art results on benchmark datasets. ⏩ Abstract: Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a particular context. Traditional supervised methods rarely take into consideration the lexical resources like WordNet, which are widely utilized in knowledge-based methods. Recent studies have shown the effectiveness of incorporating gloss (sense definition) into neural networks for WSD. However, compared with traditional word expert supervised methods, they have not achieved much improvement. In this paper, we focus on how to better leverage gloss knowledge in a supervised neural WSD system. We construct context-gloss pairs and propose three BERT-based models for WSD. We fine-tune the pre-trained BERT model on SemCor3.0 training corpus and the experimental results on several English all-words WSD benchmark datasets show that our approach outperforms the state-of-the-art systems. Please feel free to share out the content and subscribe to my channel :) ⏩ Subscribe - https://youtube.com/channel/UCoz8NrwgL7U9535VNc0mRPA?sub_confirmation=1 ⏩ OUTLINE: 0:00 - Abstract 01:46 - Task Definition 02:11 - Data Collection approach 02:30 - WordNet Overview 03:35 - Sentence construction method table overview 05:27 - BERT(Token-CLS) 06:41 - GlossBERT 07:52 - Context-Gloss Pair with Weak Supervision 08:55 - GlossBERT(Token-CLS) 09:20 - GlossBERT(Sent-CLS) 09:44 - GlossBERT(Sent-CLS-WS) 10:09 - Results ⏩ Paper Title: GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge ⏩ Paper: https://arxiv.org/abs/1908.07245v4 ⏩ Code: https://github.com/HSLCY/GlossBERT ⏩ Author: Luyao Huang, Chi Sun, Xipeng Qiu, Xuanjing Huang ⏩ Organisation: Fudan University ⏩ IMPORTANT LINKS Full Playlist on BERT usecases in NLP: https://www.youtube.com/watch?v=kC5kP1dPAzc&list=PLsAqq9lZFOtV8jYq3JlkqPQUN5QxcWq0f Full Playlist on Text Data Augmentation Techniques: https://www.youtube.com/watch?v=9O9scQb4sNo&list=PLsAqq9lZFOtUg63g_95OuV-R2GhV1UiIZ Full Playlist on Text Summarization: https://www.youtube.com/watch?v=kC5kP1dPAzc&list=PLsAqq9lZFOtV8jYq3JlkqPQUN5QxcWq0f Full Playlist on Machine Learning with Graphs: https://www.youtube.com/watch?v=-uJL_ANy1jc&list=PLsAqq9lZFOtU7tT6mDXX_fhv1R1-jGiYf Full Playlist on Evaluating NLG Systems: https://www.youtube.com/watch?v=-CIlz-5um7U&list=PLsAqq9lZFOtXlzg5RNyV00ueE89PwnCbu ********************************************* If you want to support me financially which totally optional and voluntary :) ❤️ You can consider buying me chai ( because i don't drink coffee :) ) at https://www.buymeacoffee.com/TechvizCoffee ********************************************* ⏩ Youtube - https://www.youtube.com/c/TechVizTheDataScienceGuy ⏩ Blog - https://prakhartechviz.blogspot.com ⏩ LinkedIn - https://linkedin.com/in/prakhar21 ⏩ Medium - https://medium.com/@prakhar.mishra ⏩ GitHub - https://github.com/prakhar21 ⏩ Twitter - https://twitter.com/rattller ********************************************* Please feel free to share out the content and subscribe to my channel :) ⏩ Subscribe - https://youtube.com/channel/UCoz8NrwgL7U9535VNc0mRPA?sub_confirmation=1 Tools I use for making videos :) ⏩ iPad - https://tinyurl.com/y39p6pwc ⏩ Apple Pencil - https://tinyurl.com/y5rk8txn ⏩ GoodNotes - https://tinyurl.com/y627cfsa #techviz #datascienceguy #ai #researchpaper #naturallanguageprocessing #bart

• published: 07 Apr 2021
• views: 2095

35:11

093 Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge - NODES2022

• Order: Reorder
• Duration: 35:11
• Uploaded Date: 30 Nov 2022
• views: 515

Natural language processing is an indispensable toolkit to build knowledge graphs from unstructured data. However, it comes with a price. Keywords and entities ...

Natural language processing is an indispensable toolkit to build knowledge graphs from unstructured data. However, it comes with a price. Keywords and entities in unstructured texts are ambiguous - the same concept can be expressed by many different linguistic variations. The resulting knowledge graph would thus be polluted with many nodes representing the same entity without any order. In this session, we show how the semantic similarity based on transformer embeddings and agglomerative clustering can help in the domain of academic disciplines and research fields and how Neo4j improves the browsing experience of this knowledge graph. Speakers: Federica Ventruto, Alessia Melania Lonoce Format: Full Session 30-45 min Level: Advanced Topics: #KnowledgeGraph, #MachineLearning, #Visualization, #General, #Advanced Region: EMEA Slides: https://dist.neo4j.com/nodes-20202-slides/093%20Keyword%20Disambiguation%20Using%20Transformers%20and%20Clustering%20to%20Build%20Cleaner%20Knowledge%20Graphs%20-%20NODES2022%20EMEA%20Advanced%206%20-%20Federica%20Ventruto%2C%20Alessia%20Melania%20Lonoce.pdf Visit https://neo4j.com/nodes-2022 learn more at https://neo4j.com/developer/get-started and engage at https://community.neo4j.com

https://wn.com/093_Keyword_Disambiguation_Using_Transformers_And_Clustering_To_Build_Cleaner_Knowledge_Nodes2022

Natural language processing is an indispensable toolkit to build knowledge graphs from unstructured data. However, it comes with a price. Keywords and entities in unstructured texts are ambiguous - the same concept can be expressed by many different linguistic variations. The resulting knowledge graph would thus be polluted with many nodes representing the same entity without any order. In this session, we show how the semantic similarity based on transformer embeddings and agglomerative clustering can help in the domain of academic disciplines and research fields and how Neo4j improves the browsing experience of this knowledge graph. Speakers: Federica Ventruto, Alessia Melania Lonoce Format: Full Session 30-45 min Level: Advanced Topics: #KnowledgeGraph, #MachineLearning, #Visualization, #General, #Advanced Region: EMEA Slides: https://dist.neo4j.com/nodes-20202-slides/093%20Keyword%20Disambiguation%20Using%20Transformers%20and%20Clustering%20to%20Build%20Cleaner%20Knowledge%20Graphs%20-%20NODES2022%20EMEA%20Advanced%206%20-%20Federica%20Ventruto%2C%20Alessia%20Melania%20Lonoce.pdf Visit https://neo4j.com/nodes-2022 learn more at https://neo4j.com/developer/get-started and engage at https://community.neo4j.com

• published: 30 Nov 2022
• views: 515

8:29

Word Sense Disambiguation 🔥

• Order: Reorder
• Duration: 8:29
• Uploaded Date: 05 Dec 2021
• views: 62029

This video tutorial is about Word Sense Disambiguation in Natural Language Processing ( nlp ) in the language Hindi using lesk algorithm. Purchase notes right ...

This video tutorial is about Word Sense Disambiguation in Natural Language Processing ( nlp ) in the language Hindi using lesk algorithm. Purchase notes right now, more details below: https://perfectcomputerengineer.classx.co.in/new-courses/13-natural-language-processing-notes * Natural Language Processing Playlist: https://youtube.com/playlist?list=PLPIwNooIb9vimsumdWeKF3BRzs9tJ-_gy * Human-Machine Interaction entire Playlist: https://www.youtube.com/playlist?list=PLPIwNooIb9vhFRT_3JDQ0CGbW5HeFg3yK * Distributed Computing: https://youtube.com/playlist?list=PLPIwNooIb9vhYroMrNpoBYiBUFzTwEZot *Gears used for this YouTube Channel: https://linktr.ee/perfectcomputerengineer *Let's connect: Instagram: https://www.instagram.com/planetojas/

https://wn.com/Word_Sense_Disambiguation_🔥

This video tutorial is about Word Sense Disambiguation in Natural Language Processing ( nlp ) in the language Hindi using lesk algorithm. Purchase notes right now, more details below: https://perfectcomputerengineer.classx.co.in/new-courses/13-natural-language-processing-notes * Natural Language Processing Playlist: https://youtube.com/playlist?list=PLPIwNooIb9vimsumdWeKF3BRzs9tJ-_gy * Human-Machine Interaction entire Playlist: https://www.youtube.com/playlist?list=PLPIwNooIb9vhFRT_3JDQ0CGbW5HeFg3yK * Distributed Computing: https://youtube.com/playlist?list=PLPIwNooIb9vhYroMrNpoBYiBUFzTwEZot *Gears used for this YouTube Channel: https://linktr.ee/perfectcomputerengineer *Let's connect: Instagram: https://www.instagram.com/planetojas/

• published: 05 Dec 2021
• views: 62029

2:57

Technical Track: gambit – An Open Source Name Disambiguation Tool for Version Control Systems

• Order: Reorder
• Duration: 2:57
• Uploaded Date: 01 Jun 2021
• views: 18

Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose ga...

Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose gambit, a rule-based disambiguation tool that only relies on name and email information. We evaluate its performance against two commonly used algorithms with similar characteristics, on manually disambiguated ground-truth data from the Gnome GTK project. Our results show that gambit significantly outperforms both algorithms in terms of precision as well as F1 score. Uploaded with Clowdr https://clowdr.org/

https://wn.com/Technical_Track_Gambit_–_An_Open_Source_Name_Disambiguation_Tool_For_Version_Control_Systems

Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose gambit, a rule-based disambiguation tool that only relies on name and email information. We evaluate its performance against two commonly used algorithms with similar characteristics, on manually disambiguated ground-truth data from the Gnome GTK project. Our results show that gambit significantly outperforms both algorithms in terms of precision as well as F1 score. Uploaded with Clowdr https://clowdr.org/

• published: 01 Jun 2021
• views: 18

9:52

Data-centric disambiguation for data transformation with programming-by-example

• Order: Reorder
• Duration: 9:52
• Uploaded Date: 29 Apr 2021
• views: 63

Data-centric disambiguation for data transformation with programming-by-example Minori Narita, Nolwenn Maudet, Yi Lu, Takeo Igarashi 26th ACM International Con...

Data-centric disambiguation for data transformation with programming-by-example Minori Narita, Nolwenn Maudet, Yi Lu, Takeo Igarashi 26th ACM International Conference on Intelligent User Interfaces (IUI '21) Session: AI in Education & Intelligent Tutoring System Abstract Programming-by-example (PBE), can be a powerful tool to reduce manual work in repetitive data transformation tasks. However, few examples often leave ambiguity and may cause undesirable data transformation by the system. This ambiguity can be resolved by allowing the user to directly edit the synthesized programs; however, this is difficult for non-programmers. Here, we present a novel approach: data-centric disambiguation for data transformation, where users resolve the ambiguity in data transformation by examining and modifying the output rather than the program. The key idea is to focus on the given set of data the user wants to transform instead of pursuing the synthesized program’s generality or completeness. Our system provides visualization and interaction methods that allow users to efficiently examine and fix the transformed outputs, which is much simpler than understanding and modifying the program itself. The user study suggests that our system can successfully help non-programmers to more easily and efficiently process data. DOI:: https://doi.org/10.1145/3397481.3450680 WEB:: https://iui.acm.org/2021 Pre-recorded presentation videos for IUI 2021.

https://wn.com/Data_Centric_Disambiguation_For_Data_Transformation_With_Programming_By_Example

Data-centric disambiguation for data transformation with programming-by-example Minori Narita, Nolwenn Maudet, Yi Lu, Takeo Igarashi 26th ACM International Conference on Intelligent User Interfaces (IUI '21) Session: AI in Education & Intelligent Tutoring System Abstract Programming-by-example (PBE), can be a powerful tool to reduce manual work in repetitive data transformation tasks. However, few examples often leave ambiguity and may cause undesirable data transformation by the system. This ambiguity can be resolved by allowing the user to directly edit the synthesized programs; however, this is difficult for non-programmers. Here, we present a novel approach: data-centric disambiguation for data transformation, where users resolve the ambiguity in data transformation by examining and modifying the output rather than the program. The key idea is to focus on the given set of data the user wants to transform instead of pursuing the synthesized program’s generality or completeness. Our system provides visualization and interaction methods that allow users to efficiently examine and fix the transformed outputs, which is much simpler than understanding and modifying the program itself. The user study suggests that our system can successfully help non-programmers to more easily and efficiently process data. DOI:: https://doi.org/10.1145/3397481.3450680 WEB:: https://iui.acm.org/2021 Pre-recorded presentation videos for IUI 2021.

• published: 29 Apr 2021
• views: 63

33:56

Disambiguation: AI and the Customer Journey

• Order: Reorder
• Duration: 33:56
• Uploaded Date: 10 Nov 2023
• views: 44

AI and Generative AI have huge potential to help businesses improve the entire customer lifecycle. I'm joined by AI, CRM and process automation expert Jeff Nich...

AI and Generative AI have huge potential to help businesses improve the entire customer lifecycle. I'm joined by AI, CRM and process automation expert Jeff Nicholson for a wide ranging discussion on AI and generative AI in sales, marketing and customer service and how the application of these technologies can enhance the customer journey.

https://wn.com/Disambiguation_Ai_And_The_Customer_Journey

AI and Generative AI have huge potential to help businesses improve the entire customer lifecycle. I'm joined by AI, CRM and process automation expert Jeff Nicholson for a wide ranging discussion on AI and generative AI in sales, marketing and customer service and how the application of these technologies can enhance the customer journey.

• published: 10 Nov 2023
• views: 44

24:46

KGC 2022: KG-Based Approach to Named Entity Disambiguation for Healthcare Applications — GraphAware

• Order: Reorder
• Duration: 24:46
• Uploaded Date: 03 Nov 2022
• views: 389

Senior Data Scientist at GraphAware, Giuseppe Futia, shows how to leverage a Named Entity Disambiguation (NED) system to disambiguate named entities in the heal...

Senior Data Scientist at GraphAware, Giuseppe Futia, shows how to leverage a Named Entity Disambiguation (NED) system to disambiguate named entities in the healthcare domain and combine multiple knowledge graphs and ontologies in a single valuable source of truth. The approach incorporates node embeddings into the NED model, employing the KG structure for the training process. The tool can support different healthcare applications, including literature search and retrieval, clinical decision-making, relational knowledge findings, chatbots for health assistance, and recommendation tools for patients and medical practitioners. Giuseppe Futia holds a Ph.D. in Computer Engineering from the Politecnico di Torino, where he explored Graph Representation Learning techniques to support the automatic building of Knowledge Graphs. The 5 key takeaways: 1. The components and requirements of the Intelligent Advisory Systems (IAS). 2. How they use Hume, the Neo4j-backed no-code knowledge graph ecosystem. 3. Delving into diabetes real-life use cases and linking to the Unified Medical Language System. 4. How GraphAware utilizes ontology-based enrichment for their knowledge graph-based approach. 5. The cooperation of NED candidates selections and NED candidates ranking. #biotechnology #lifescience #technology

https://wn.com/Kgc_2022_Kg_Based_Approach_To_Named_Entity_Disambiguation_For_Healthcare_Applications_—_Graphaware

Senior Data Scientist at GraphAware, Giuseppe Futia, shows how to leverage a Named Entity Disambiguation (NED) system to disambiguate named entities in the healthcare domain and combine multiple knowledge graphs and ontologies in a single valuable source of truth. The approach incorporates node embeddings into the NED model, employing the KG structure for the training process. The tool can support different healthcare applications, including literature search and retrieval, clinical decision-making, relational knowledge findings, chatbots for health assistance, and recommendation tools for patients and medical practitioners. Giuseppe Futia holds a Ph.D. in Computer Engineering from the Politecnico di Torino, where he explored Graph Representation Learning techniques to support the automatic building of Knowledge Graphs. The 5 key takeaways: 1. The components and requirements of the Intelligent Advisory Systems (IAS). 2. How they use Hume, the Neo4j-backed no-code knowledge graph ecosystem. 3. Delving into diabetes real-life use cases and linking to the Unified Medical Language System. 4. How GraphAware utilizes ontology-based enrichment for their knowledge graph-based approach. 5. The cooperation of NED candidates selections and NED candidates ranking. #biotechnology #lifescience #technology

• published: 03 Nov 2022
• views: 389

2:24:42

ApplyAI Hands-on in NLP: Word Disambiguation and Automatic Summarization

• Order: Reorder
• Duration: 2:24:42
• Uploaded Date: 09 May 2020
• views: 1382

You can find the Google Drive folder with the notebooks here: https://drive.google.com/drive/folders/1paIso1fqasLblXgjvkzOwEns4cO81ipc

You can find the Google Drive folder with the notebooks here: https://drive.google.com/drive/folders/1paIso1fqasLblXgjvkzOwEns4cO81ipc

https://wn.com/Applyai_Hands_On_In_Nlp_Word_Disambiguation_And_Automatic_Summarization

You can find the Google Drive folder with the notebooks here: https://drive.google.com/drive/folders/1paIso1fqasLblXgjvkzOwEns4cO81ipc

• published: 09 May 2020
• views: 1382

6:28

Answer me this: Constructing Disambiguation Queries for Explanation Generation in Robotics

• Order: Reorder
• Duration: 6:28
• Uploaded Date: 16 Dec 2020
• views: 30

PlanSIG 2020 ( https://plansig2020.wordpress.com/ ) Mohan Sridharan and Tiago Mota Answer me this: Constructing Disambiguation Queries for Explanation Generat...

PlanSIG 2020 ( https://plansig2020.wordpress.com/ ) Mohan Sridharan and Tiago Mota Answer me this: Constructing Disambiguation Queries for Explanation Generation in Robotics

https://wn.com/Answer_Me_This_Constructing_Disambiguation_Queries_For_Explanation_Generation_In_Robotics

PlanSIG 2020 ( https://plansig2020.wordpress.com/ ) Mohan Sridharan and Tiago Mota Answer me this: Constructing Disambiguation Queries for Explanation Generation in Robotics

• published: 16 Dec 2020
• views: 30

50:07

Mod-01 Lec-33 Word Sense Disambiguation; Overlap Based Method; Supervised Method

• Order: Reorder
• Duration: 50:07
• Uploaded Date: 03 Jul 2012
• views: 3533

Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel...

Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in

https://wn.com/Mod_01_Lec_33_Word_Sense_Disambiguation_Overlap_Based_Method_Supervised_Method

Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in

• published: 03 Jul 2012
• views: 3533

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Angie Velasco - HELL NO feat. Nico Valdi (Video Oficial)

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• Duration: 2:46
• Uploaded Date: 06 Nov 2020
• views: 10635145

Angie Velasco - HELL NO feat. Nico Valdi ♫ Disponible en Spotify Mis redes sociales: TWITTER: https://twitter.com/AngieVelasco08 INSTAGRAM: https://www.insta...

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• published: 06 Nov 2020
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3:19

Spice - Hell No (Official Audio)

• Order: Reorder
• Duration: 3:19
• Uploaded Date: 09 Aug 2024
• views: 21145

Listen to the album “Mirror 25". Out Now! Stream: https://music.empi.re/mirror25 #Spice #Mirror25 Official Audio by Spice from "Mirror 25" © 2024 S...

Listen to the album “Mirror 25". Out Now! Stream: https://music.empi.re/mirror25 #Spice #Mirror25 Official Audio by Spice from "Mirror 25" © 2024 Spice Official Entertainment

https://wn.com/Spice_Hell_No_(Official_Audio)

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4:23

Team Hell No's 5 greatest moments

• Order: Reorder
• Duration: 4:23
• Uploaded Date: 01 Jul 2018
• views: 2154107

Celebrate the reunion of Team Hell No with 5 of Daniel Bryan & Kane's best moments as a tag team, including their trip to anger management class. Get your first...

Celebrate the reunion of Team Hell No with 5 of Daniel Bryan & Kane's best moments as a tag team, including their trip to anger management class. Get your first month of WWE Network for FREE: http://wwenetwork.com Subscribe to WWE on YouTube: http://bit.ly/1i64OdT Visit WWE.com: http://goo.gl/akf0J4 Must-See WWE videos on YouTube: https://goo.gl/QmhBof

https://wn.com/Team_Hell_No's_5_Greatest_Moments

Celebrate the reunion of Team Hell No with 5 of Daniel Bryan & Kane's best moments as a tag team, including their trip to anger management class. Get your first month of WWE Network for FREE: http://wwenetwork.com Subscribe to WWE on YouTube: http://bit.ly/1i64OdT Visit WWE.com: http://goo.gl/akf0J4 Must-See WWE videos on YouTube: https://goo.gl/QmhBof

• published: 01 Jul 2018
• views: 2154107

3:09

SAABIROSE - HELL NO (prod. by KADO) | OFFICIAL MUSIC VIDEO

• Order: Reorder
• Duration: 3:09
• Uploaded Date: 04 Jul 2024
• views: 83274

SAABIROSE - HELL NO (prod. by KADO ) | OFFICIAL MUSIC VIDEO #HellNo #saabirose #Kado #SMEVN #Paume #Antiantiart https://smevn.lnk.to/HN-SBR - Spotify: https:/...

SAABIROSE - HELL NO (prod. by KADO ) | OFFICIAL MUSIC VIDEO #HellNo #saabirose #Kado #SMEVN #Paume #Antiantiart https://smevn.lnk.to/HN-SBR - Spotify: https://smevn.lnk.to/HN-SBR/spotify - Apple Music: https://smevn.lnk.to/HN-SBR/applemusic - iTunes: https://smevn.lnk.to/HN-SBR/itunes - YouTube: https://smevn.lnk.to/HN-SBR/youtube - YouTube Music: https://smevn.lnk.to/HN-SBR/youtubemusic - TikTok: https://smevn.lnk.to/HN-SBR/tiktok - Nhaccuatui: https://smevn.lnk.to/HN-SBR/nct - Zing MP3: https://smevn.lnk.to/HN-SBR/zingmp3 HELL NO | Official Music Video Music Production Singer & Composer: Saabirose Producers: Kado, Saabirose Mixing & Mastering: D.A Recorder: Đỗ Cẩm Khang Director: Romain Khanh Co-Director: Luu Anh Creative Director: Võ Ngọc Thuỵ Vân 1st Assistant Director: Thức (Antiantiart) Director of Photography: Trunduc (Antiantiart) Production House: Antiantiart & P92 Executive Producer: An Khang (Antiantiart) Executive Producer: Tuan Hô (P92 & Paume.) Producer: Giovi Phùng (Antiantiart) Line Producer: Anh Quốc (Antiantiart), Đinh Ngọc Anh Production Assistant: Tiến Đạt, Chung Nghĩa Location Manager: Hoàng Anh Art Department: Vidùa studio Art Director: Huệ Phương Art Assistant: Diệu Linh Set Decorators: Vũ Khôi Nguyên, Nguyễn Bá Ngọc, bùi hải an Stylist: Nekoh Stylist Assistant: Duhan Costume: Fanci, Lalune, Nekoh, Cailishyn, JAGA, Century, Outofsight, Elno Costume Designed by: Dang Viet Tung (Sequeen Dance Costome) Makeup Artist: Thuỷ Tiên Dance Producer: Xoăn Choreographer: 1metbontam Dancers: MADKIDZ Casts: Bii, Lưu Sơn, Quang Sơn, Công Minh, Nhật Vượng Camera & Lighting Equipment: CineHanoi Camera Operator: Phú Long Gaffer: Ngô Bá Trung (CineHanoi) Assistant Camera: Lê Văn Quỳnh, Nguyễn Văn Huy (CineHanoi) Lighting-Grip: Ngô Bá Dũng, Quách Văn Hiếu, Trần Công Phả DIT: Lương Thiên Lương Behind the Scene: Dzung Tran (Antiantiart) Post Production: Paume Post Producer: Tiffany Jacquier, Romain Algisi VFX Supervisor: Melchior Leroux VFX Artist: Kilian Pini 3D artist: Titouan Fourreau Editor: Eugène Signoret Assistant Editor: Maé Bragnier -------------------------------------- Theo dõi Saabirose tại: ► Đăng ký kênh tại đây: https://youtube.com/@Saabirose?si=okh8wo0K-t4EJJrt ► Facebook: https://www.facebook.com/saa2322 ► Fanpage: https://www.facebook.com/SaaSaaOfficial/ ► Instagram: https://www.instagram.com/saabirose22__/ ► Tiktok: www.tiktok.com/@saabirose22 --------------------- © Bản quyền thuộc về Saabirose © Copyright by Saabirose ☞ Do not reup

https://wn.com/Saabirose_Hell_No_(Prod._By_Kado)_|_Official_Music_Video

SAABIROSE - HELL NO (prod. by KADO ) | OFFICIAL MUSIC VIDEO #HellNo #saabirose #Kado #SMEVN #Paume #Antiantiart https://smevn.lnk.to/HN-SBR - Spotify: https://smevn.lnk.to/HN-SBR/spotify - Apple Music: https://smevn.lnk.to/HN-SBR/applemusic - iTunes: https://smevn.lnk.to/HN-SBR/itunes - YouTube: https://smevn.lnk.to/HN-SBR/youtube - YouTube Music: https://smevn.lnk.to/HN-SBR/youtubemusic - TikTok: https://smevn.lnk.to/HN-SBR/tiktok - Nhaccuatui: https://smevn.lnk.to/HN-SBR/nct - Zing MP3: https://smevn.lnk.to/HN-SBR/zingmp3 HELL NO | Official Music Video Music Production Singer & Composer: Saabirose Producers: Kado, Saabirose Mixing & Mastering: D.A Recorder: Đỗ Cẩm Khang Director: Romain Khanh Co-Director: Luu Anh Creative Director: Võ Ngọc Thuỵ Vân 1st Assistant Director: Thức (Antiantiart) Director of Photography: Trunduc (Antiantiart) Production House: Antiantiart & P92 Executive Producer: An Khang (Antiantiart) Executive Producer: Tuan Hô (P92 & Paume.) Producer: Giovi Phùng (Antiantiart) Line Producer: Anh Quốc (Antiantiart), Đinh Ngọc Anh Production Assistant: Tiến Đạt, Chung Nghĩa Location Manager: Hoàng Anh Art Department: Vidùa studio Art Director: Huệ Phương Art Assistant: Diệu Linh Set Decorators: Vũ Khôi Nguyên, Nguyễn Bá Ngọc, bùi hải an Stylist: Nekoh Stylist Assistant: Duhan Costume: Fanci, Lalune, Nekoh, Cailishyn, JAGA, Century, Outofsight, Elno Costume Designed by: Dang Viet Tung (Sequeen Dance Costome) Makeup Artist: Thuỷ Tiên Dance Producer: Xoăn Choreographer: 1metbontam Dancers: MADKIDZ Casts: Bii, Lưu Sơn, Quang Sơn, Công Minh, Nhật Vượng Camera & Lighting Equipment: CineHanoi Camera Operator: Phú Long Gaffer: Ngô Bá Trung (CineHanoi) Assistant Camera: Lê Văn Quỳnh, Nguyễn Văn Huy (CineHanoi) Lighting-Grip: Ngô Bá Dũng, Quách Văn Hiếu, Trần Công Phả DIT: Lương Thiên Lương Behind the Scene: Dzung Tran (Antiantiart) Post Production: Paume Post Producer: Tiffany Jacquier, Romain Algisi VFX Supervisor: Melchior Leroux VFX Artist: Kilian Pini 3D artist: Titouan Fourreau Editor: Eugène Signoret Assistant Editor: Maé Bragnier -------------------------------------- Theo dõi Saabirose tại: ► Đăng ký kênh tại đây: https://youtube.com/@Saabirose?si=okh8wo0K-t4EJJrt ► Facebook: https://www.facebook.com/saa2322 ► Fanpage: https://www.facebook.com/SaaSaaOfficial/ ► Instagram: https://www.instagram.com/saabirose22__/ ► Tiktok: www.tiktok.com/@saabirose22 --------------------- © Bản quyền thuộc về Saabirose © Copyright by Saabirose ☞ Do not reup

• published: 04 Jul 2024
• views: 83274

0:16

Oh Hell No

• Order: Reorder
• Duration: 0:16
• Uploaded Date: 07 Apr 2009
• views: 9113633

Pushing Daisies - Emerson Cod Oh Hell No

Pushing Daisies - Emerson Cod Oh Hell No

https://wn.com/Oh_Hell_No

Pushing Daisies - Emerson Cod Oh Hell No

• published: 07 Apr 2009
• views: 9113633

3:23

HELL NO: The Sensible Horror Film

• Order: Reorder
• Duration: 3:23
• Uploaded Date: 15 Oct 2013
• views: 7744477

Imagine a realm where the most horrifying terrors of the underworld emerge to wreak bloody vengeance upon any who... hmm? what's that? you wanna go literally an...

Imagine a realm where the most horrifying terrors of the underworld emerge to wreak bloody vengeance upon any who... hmm? what's that? you wanna go literally anywhere else? yeah, good idea let's get out of here Directed by Joe Nicolosi Written by Joe Nicolosi and John Freiler Produced by Stephanie Noone Exe. Produced by Arts + Labor Director of Photography: Drew Daniels Music by Danny Gray Visual Effects by Moontower VFX, Ray Pena and Greg Omelchuck Cast: Alex Dobrenko, Ashley Spillers, Jessie Tilton, Sam Davis, Brandon Potter, Sam Eidson, Katie Folger, Sam Van Metre, Deke Garner, Jonny Mars, Zack Carlson, Bryan Connolly, David Hess, Mike Gassaway, Jason Newman, Elise Garza, April Swartz, Isaac Solomon, Marc Calderaro, Matt Van Doren, Drew Daniels, Aimee Thomas, Brock England, Jenniemarie Jemison, Clay Crenshaw, Andrew Matthews, Katie Graham, Will Elliott, Mallory Culbert, Joey Hood Assistant Director: Thomas Fernandes Gaffer: Emmett Kerr-Perkinson Art Department: April Swartz, Elise Garza, Stephanie Noone Assistant Camera: Zach Sprague Key Grip: Matt Van Doren Sound Recordist: Landry Gideon Sound Designer: Eric Friend Colorist / Online Editor: Daniel Stuyck Special Thanks: Kate Eads, Erik Horn, Derek Gildersleeve, Willie Rockefeller, Alan Berg, Zach Loeb, Derrick & Shareina Garner, Clay Liford, Bradley Jackson, Dave Ward, Kayla Kromer, Tony Brummer, Andy Young ,Don Swanos, Owen Egerton, Kirk Johnson, Peter Dealbert, Isaac Solomon, Sarah Siegel, Thomas Humphreys, Zilker Park Boat Rentals Great Hall Games, Quonset Hut, Delta Millworks

https://wn.com/Hell_No_The_Sensible_Horror_Film

Imagine a realm where the most horrifying terrors of the underworld emerge to wreak bloody vengeance upon any who... hmm? what's that? you wanna go literally anywhere else? yeah, good idea let's get out of here Directed by Joe Nicolosi Written by Joe Nicolosi and John Freiler Produced by Stephanie Noone Exe. Produced by Arts + Labor Director of Photography: Drew Daniels Music by Danny Gray Visual Effects by Moontower VFX, Ray Pena and Greg Omelchuck Cast: Alex Dobrenko, Ashley Spillers, Jessie Tilton, Sam Davis, Brandon Potter, Sam Eidson, Katie Folger, Sam Van Metre, Deke Garner, Jonny Mars, Zack Carlson, Bryan Connolly, David Hess, Mike Gassaway, Jason Newman, Elise Garza, April Swartz, Isaac Solomon, Marc Calderaro, Matt Van Doren, Drew Daniels, Aimee Thomas, Brock England, Jenniemarie Jemison, Clay Crenshaw, Andrew Matthews, Katie Graham, Will Elliott, Mallory Culbert, Joey Hood Assistant Director: Thomas Fernandes Gaffer: Emmett Kerr-Perkinson Art Department: April Swartz, Elise Garza, Stephanie Noone Assistant Camera: Zach Sprague Key Grip: Matt Van Doren Sound Recordist: Landry Gideon Sound Designer: Eric Friend Colorist / Online Editor: Daniel Stuyck Special Thanks: Kate Eads, Erik Horn, Derek Gildersleeve, Willie Rockefeller, Alan Berg, Zach Loeb, Derrick & Shareina Garner, Clay Liford, Bradley Jackson, Dave Ward, Kayla Kromer, Tony Brummer, Andy Young ,Don Swanos, Owen Egerton, Kirk Johnson, Peter Dealbert, Isaac Solomon, Sarah Siegel, Thomas Humphreys, Zilker Park Boat Rentals Great Hall Games, Quonset Hut, Delta Millworks

• published: 15 Oct 2013
• views: 7744477

3:02

Hell No - Gabriel Iglesias

• Order: Reorder
• Duration: 3:02
• Uploaded Date: 21 Jul 2022
• views: 407538

Happy Throwback Thursday

Happy Throwback Thursday

https://wn.com/Hell_No_Gabriel_Iglesias

Happy Throwback Thursday

• published: 21 Jul 2022
• views: 407538

0:19

hell naw

• Order: Reorder
• Duration: 0:19
• Uploaded Date: 26 Jan 2024
• views: 2933514

did you eat a treat? @marks.gallery

did you eat a treat? @marks.gallery

https://wn.com/Hell_Naw

did you eat a treat? @marks.gallery

• published: 26 Jan 2024
• views: 2933514

19:44

Hell NO❌⚠️

• Order: Reorder
• Duration: 19:44
• Uploaded Date: 01 Oct 2024
• views: 67

https://wn.com/Hell_No❌⚠️

• published: 01 Oct 2024
• views: 67

2:32

バカレア組 HELL,NO

• Order: Reorder
• Duration: 2:32
• Uploaded Date: 26 Mar 2013
• views: 28865

https://wn.com/バカレア組_Hell,No

• published: 26 Mar 2013
• views: 28865

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11:18

GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge (Research Paper Walkthrough)

#bert #wsd #wordnet This research uses BERT for Word Sense Disambiguation use case in NLP ...

published: 07 Apr 2021

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GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge (Research Paper Walkthrough)

GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge (Research Paper Walkthrough)

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• published: 07 Apr 2021
• views: 2095

#bert #wsd #wordnet This research uses BERT for Word Sense Disambiguation use case in NLP by modeling the entire problem as sentence classification task using the Gloss knowledge. They show state-of-art results on benchmark datasets. ⏩ Abstract: Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a particular context. Traditional supervised methods rarely take into consideration the lexical resources like WordNet, which are widely utilized in knowledge-based methods. Recent studies have shown the effectiveness of incorporating gloss (sense definition) into neural networks for WSD. However, compared with traditional word expert supervised methods, they have not achieved much improvement. In this paper, we focus on how to better leverage gloss knowledge in a supervised neural WSD system. We construct context-gloss pairs and propose three BERT-based models for WSD. We fine-tune the pre-trained BERT model on SemCor3.0 training corpus and the experimental results on several English all-words WSD benchmark datasets show that our approach outperforms the state-of-the-art systems. Please feel free to share out the content and subscribe to my channel :) ⏩ Subscribe - https://youtube.com/channel/UCoz8NrwgL7U9535VNc0mRPA?sub_confirmation=1 ⏩ OUTLINE: 0:00 - Abstract 01:46 - Task Definition 02:11 - Data Collection approach 02:30 - WordNet Overview 03:35 - Sentence construction method table overview 05:27 - BERT(Token-CLS) 06:41 - GlossBERT 07:52 - Context-Gloss Pair with Weak Supervision 08:55 - GlossBERT(Token-CLS) 09:20 - GlossBERT(Sent-CLS) 09:44 - GlossBERT(Sent-CLS-WS) 10:09 - Results ⏩ Paper Title: GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge ⏩ Paper: https://arxiv.org/abs/1908.07245v4 ⏩ Code: https://github.com/HSLCY/GlossBERT ⏩ Author: Luyao Huang, Chi Sun, Xipeng Qiu, Xuanjing Huang ⏩ Organisation: Fudan University ⏩ IMPORTANT LINKS Full Playlist on BERT usecases in NLP: https://www.youtube.com/watch?v=kC5kP1dPAzc&list=PLsAqq9lZFOtV8jYq3JlkqPQUN5QxcWq0f Full Playlist on Text Data Augmentation Techniques: https://www.youtube.com/watch?v=9O9scQb4sNo&list=PLsAqq9lZFOtUg63g_95OuV-R2GhV1UiIZ Full Playlist on Text Summarization: https://www.youtube.com/watch?v=kC5kP1dPAzc&list=PLsAqq9lZFOtV8jYq3JlkqPQUN5QxcWq0f Full Playlist on Machine Learning with Graphs: https://www.youtube.com/watch?v=-uJL_ANy1jc&list=PLsAqq9lZFOtU7tT6mDXX_fhv1R1-jGiYf Full Playlist on Evaluating NLG Systems: https://www.youtube.com/watch?v=-CIlz-5um7U&list=PLsAqq9lZFOtXlzg5RNyV00ueE89PwnCbu ********************************************* If you want to support me financially which totally optional and voluntary :) ❤️ You can consider buying me chai ( because i don't drink coffee :) ) at https://www.buymeacoffee.com/TechvizCoffee ********************************************* ⏩ Youtube - https://www.youtube.com/c/TechVizTheDataScienceGuy ⏩ Blog - https://prakhartechviz.blogspot.com ⏩ LinkedIn - https://linkedin.com/in/prakhar21 ⏩ Medium - https://medium.com/@prakhar.mishra ⏩ GitHub - https://github.com/prakhar21 ⏩ Twitter - https://twitter.com/rattller ********************************************* Please feel free to share out the content and subscribe to my channel :) ⏩ Subscribe - https://youtube.com/channel/UCoz8NrwgL7U9535VNc0mRPA?sub_confirmation=1 Tools I use for making videos :) ⏩ iPad - https://tinyurl.com/y39p6pwc ⏩ Apple Pencil - https://tinyurl.com/y5rk8txn ⏩ GoodNotes - https://tinyurl.com/y627cfsa #techviz #datascienceguy #ai #researchpaper #naturallanguageprocessing #bart

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35:11

093 Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge - NODES2022

Natural language processing is an indispensable toolkit to build knowledge graphs from uns...

published: 30 Nov 2022

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093 Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge - NODES2022

093 Keyword Disambiguation Using Transformers and Clustering to Build Cleaner Knowledge - NODES2022

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• published: 30 Nov 2022
• views: 515

Natural language processing is an indispensable toolkit to build knowledge graphs from unstructured data. However, it comes with a price. Keywords and entities in unstructured texts are ambiguous - the same concept can be expressed by many different linguistic variations. The resulting knowledge graph would thus be polluted with many nodes representing the same entity without any order. In this session, we show how the semantic similarity based on transformer embeddings and agglomerative clustering can help in the domain of academic disciplines and research fields and how Neo4j improves the browsing experience of this knowledge graph. Speakers: Federica Ventruto, Alessia Melania Lonoce Format: Full Session 30-45 min Level: Advanced Topics: #KnowledgeGraph, #MachineLearning, #Visualization, #General, #Advanced Region: EMEA Slides: https://dist.neo4j.com/nodes-20202-slides/093%20Keyword%20Disambiguation%20Using%20Transformers%20and%20Clustering%20to%20Build%20Cleaner%20Knowledge%20Graphs%20-%20NODES2022%20EMEA%20Advanced%206%20-%20Federica%20Ventruto%2C%20Alessia%20Melania%20Lonoce.pdf Visit https://neo4j.com/nodes-2022 learn more at https://neo4j.com/developer/get-started and engage at https://community.neo4j.com

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8:29

Word Sense Disambiguation 🔥

This video tutorial is about Word Sense Disambiguation in Natural Language Processing ( nl...

published: 05 Dec 2021

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Word Sense Disambiguation 🔥

Word Sense Disambiguation 🔥

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• published: 05 Dec 2021
• views: 62029

This video tutorial is about Word Sense Disambiguation in Natural Language Processing ( nlp ) in the language Hindi using lesk algorithm. Purchase notes right now, more details below: https://perfectcomputerengineer.classx.co.in/new-courses/13-natural-language-processing-notes * Natural Language Processing Playlist: https://youtube.com/playlist?list=PLPIwNooIb9vimsumdWeKF3BRzs9tJ-_gy * Human-Machine Interaction entire Playlist: https://www.youtube.com/playlist?list=PLPIwNooIb9vhFRT_3JDQ0CGbW5HeFg3yK * Distributed Computing: https://youtube.com/playlist?list=PLPIwNooIb9vhYroMrNpoBYiBUFzTwEZot *Gears used for this YouTube Channel: https://linktr.ee/perfectcomputerengineer *Let's connect: Instagram: https://www.instagram.com/planetojas/

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2:57

Technical Track: gambit – An Open Source Name Disambiguation Tool for Version Control Systems

Name disambiguation is a complex but highly relevant challenge whenever analysing real-wor...

published: 01 Jun 2021

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Technical Track: gambit – An Open Source Name Disambiguation Tool for Version Control Systems

Technical Track: gambit – An Open Source Name Disambiguation Tool for Version Control Systems

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• published: 01 Jun 2021
• views: 18

Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose gambit, a rule-based disambiguation tool that only relies on name and email information. We evaluate its performance against two commonly used algorithms with similar characteristics, on manually disambiguated ground-truth data from the Gnome GTK project. Our results show that gambit significantly outperforms both algorithms in terms of precision as well as F1 score. Uploaded with Clowdr https://clowdr.org/

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9:52

Data-centric disambiguation for data transformation with programming-by-example

Data-centric disambiguation for data transformation with programming-by-example Minori Nar...

published: 29 Apr 2021

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Data-centric disambiguation for data transformation with programming-by-example

Data-centric disambiguation for data transformation with programming-by-example

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• published: 29 Apr 2021
• views: 63

Data-centric disambiguation for data transformation with programming-by-example Minori Narita, Nolwenn Maudet, Yi Lu, Takeo Igarashi 26th ACM International Conference on Intelligent User Interfaces (IUI '21) Session: AI in Education & Intelligent Tutoring System Abstract Programming-by-example (PBE), can be a powerful tool to reduce manual work in repetitive data transformation tasks. However, few examples often leave ambiguity and may cause undesirable data transformation by the system. This ambiguity can be resolved by allowing the user to directly edit the synthesized programs; however, this is difficult for non-programmers. Here, we present a novel approach: data-centric disambiguation for data transformation, where users resolve the ambiguity in data transformation by examining and modifying the output rather than the program. The key idea is to focus on the given set of data the user wants to transform instead of pursuing the synthesized program’s generality or completeness. Our system provides visualization and interaction methods that allow users to efficiently examine and fix the transformed outputs, which is much simpler than understanding and modifying the program itself. The user study suggests that our system can successfully help non-programmers to more easily and efficiently process data. DOI:: https://doi.org/10.1145/3397481.3450680 WEB:: https://iui.acm.org/2021 Pre-recorded presentation videos for IUI 2021.

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33:56

Disambiguation: AI and the Customer Journey

AI and Generative AI have huge potential to help businesses improve the entire customer li...

published: 10 Nov 2023

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Disambiguation: AI and the Customer Journey

Disambiguation: AI and the Customer Journey

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• published: 10 Nov 2023
• views: 44

AI and Generative AI have huge potential to help businesses improve the entire customer lifecycle. I'm joined by AI, CRM and process automation expert Jeff Nicholson for a wide ranging discussion on AI and generative AI in sales, marketing and customer service and how the application of these technologies can enhance the customer journey.

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24:46

KGC 2022: KG-Based Approach to Named Entity Disambiguation for Healthcare Applications — GraphAware

Senior Data Scientist at GraphAware, Giuseppe Futia, shows how to leverage a Named Entity ...

published: 03 Nov 2022

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KGC 2022: KG-Based Approach to Named Entity Disambiguation for Healthcare Applications — GraphAware

KGC 2022: KG-Based Approach to Named Entity Disambiguation for Healthcare Applications — GraphAware

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• published: 03 Nov 2022
• views: 389

Senior Data Scientist at GraphAware, Giuseppe Futia, shows how to leverage a Named Entity Disambiguation (NED) system to disambiguate named entities in the healthcare domain and combine multiple knowledge graphs and ontologies in a single valuable source of truth. The approach incorporates node embeddings into the NED model, employing the KG structure for the training process. The tool can support different healthcare applications, including literature search and retrieval, clinical decision-making, relational knowledge findings, chatbots for health assistance, and recommendation tools for patients and medical practitioners. Giuseppe Futia holds a Ph.D. in Computer Engineering from the Politecnico di Torino, where he explored Graph Representation Learning techniques to support the automatic building of Knowledge Graphs. The 5 key takeaways: 1. The components and requirements of the Intelligent Advisory Systems (IAS). 2. How they use Hume, the Neo4j-backed no-code knowledge graph ecosystem. 3. Delving into diabetes real-life use cases and linking to the Unified Medical Language System. 4. How GraphAware utilizes ontology-based enrichment for their knowledge graph-based approach. 5. The cooperation of NED candidates selections and NED candidates ranking. #biotechnology #lifescience #technology

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2:24:42

ApplyAI Hands-on in NLP: Word Disambiguation and Automatic Summarization

You can find the Google Drive folder with the notebooks here: https://drive.google.com/dri...

published: 09 May 2020

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ApplyAI Hands-on in NLP: Word Disambiguation and Automatic Summarization

ApplyAI Hands-on in NLP: Word Disambiguation and Automatic Summarization

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• published: 09 May 2020
• views: 1382

You can find the Google Drive folder with the notebooks here: https://drive.google.com/drive/folders/1paIso1fqasLblXgjvkzOwEns4cO81ipc

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6:28

Answer me this: Constructing Disambiguation Queries for Explanation Generation in Robotics

PlanSIG 2020 ( https://plansig2020.wordpress.com/ ) Mohan Sridharan and Tiago Mota Answe...

published: 16 Dec 2020

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Answer me this: Constructing Disambiguation Queries for Explanation Generation in Robotics

Answer me this: Constructing Disambiguation Queries for Explanation Generation in Robotics

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• published: 16 Dec 2020
• views: 30

PlanSIG 2020 ( https://plansig2020.wordpress.com/ ) Mohan Sridharan and Tiago Mota Answer me this: Constructing Disambiguation Queries for Explanation Generation in Robotics

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50:07

Mod-01 Lec-33 Word Sense Disambiguation; Overlap Based Method; Supervised Method

Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science...

published: 03 Jul 2012

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Mod-01 Lec-33 Word Sense Disambiguation; Overlap Based Method; Supervised Method

Mod-01 Lec-33 Word Sense Disambiguation; Overlap Based Method; Supervised Method

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• published: 03 Jul 2012
• views: 3533

Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in

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Answering machine

The answering machine, answerphone or message machine, also known as the telephone answering machine (or TAM) in the UK and some Commonwealth countries, ansaphone or ansafone (from a trade name), or telephone answering device (TAD) is a device for answering telephones and recording callers' messages.

Unlike voicemail, which can be a centralized or networked system that performs a similar function, an answering machine must be set up in the user's premises alongside — or incorporated within — the user's telephone.

History

The tape answering machine records and replays sound using a technique originally invented in 1898 by Valdemar Poulsen which was the first practical device used for recording telephone conversations. Poulsen's device, known as a telegraphone or 'wire recorder', laid the foundation for the invention of the answering machines used today (though it was also used to record dictation and even music.) The creation of the first practical automatic answering device for telephones is in dispute. Clarence Hickman worked for Bell Laboratories from 1930 where he developed methods for the magnetic recording and working on the recognition of speech patterns and electromechanical switching systems. In 1934 he developed a tape-based answering machine which the phone company AT&T, as the owner of Bell Laboratories, kept under wraps for years for fears that an answering machine would result in fewer telephone calls. Many claim it was William Muller in 1935, but it could have been created already in 1931 by William Schergens whose device used phonographic cylinders.Ludwig Blattner promoted a telephone answering machine in 1929 based on his Blattnerphone magnetic recording technology.

Read more

This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Answering_machine

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2:46

Angie Velasco - HELL NO feat. Nico Valdi (Video Oficial)

Angie Velasco - HELL NO feat. Nico Valdi ♫ Disponible en Spotify Mis redes sociales: TWI...

published: 06 Nov 2020

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Angie Velasco - HELL NO feat. Nico Valdi (Video Oficial)

Angie Velasco - HELL NO feat. Nico Valdi (Video Oficial)

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Angie Velasco - HELL NO feat. Nico Valdi ♫ Disponible en Spotify Mis redes sociales: TWITTER: https://twitter.com/AngieVelasco08 INSTAGRAM: https://www.instagram.com/angievelasco08 SPICYLEMON: https://spicylemon.com.ar/

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3:19

Spice - Hell No (Official Audio)

Listen to the album “Mirror 25". Out Now! Stream: https://music.empi.re/mirror25 #Spice...

published: 09 Aug 2024

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Spice - Hell No (Official Audio)

Spice - Hell No (Official Audio)

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Listen to the album “Mirror 25". Out Now! Stream: https://music.empi.re/mirror25 #Spice #Mirror25 Official Audio by Spice from "Mirror 25" © 2024 Spice Official Entertainment

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4:23

Team Hell No's 5 greatest moments

Celebrate the reunion of Team Hell No with 5 of Daniel Bryan & Kane's best moments as a ta...

published: 01 Jul 2018

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Team Hell No's 5 greatest moments

Team Hell No's 5 greatest moments

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Celebrate the reunion of Team Hell No with 5 of Daniel Bryan & Kane's best moments as a tag team, including their trip to anger management class. Get your first month of WWE Network for FREE: http://wwenetwork.com Subscribe to WWE on YouTube: http://bit.ly/1i64OdT Visit WWE.com: http://goo.gl/akf0J4 Must-See WWE videos on YouTube: https://goo.gl/QmhBof

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3:09

SAABIROSE - HELL NO (prod. by KADO) | OFFICIAL MUSIC VIDEO

SAABIROSE - HELL NO (prod. by KADO ) | OFFICIAL MUSIC VIDEO #HellNo #saabirose #Kado #SMEV...

published: 04 Jul 2024

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SAABIROSE - HELL NO (prod. by KADO) | OFFICIAL MUSIC VIDEO

SAABIROSE - HELL NO (prod. by KADO) | OFFICIAL MUSIC VIDEO

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SAABIROSE - HELL NO (prod. by KADO ) | OFFICIAL MUSIC VIDEO #HellNo #saabirose #Kado #SMEVN #Paume #Antiantiart https://smevn.lnk.to/HN-SBR - Spotify: https://smevn.lnk.to/HN-SBR/spotify - Apple Music: https://smevn.lnk.to/HN-SBR/applemusic - iTunes: https://smevn.lnk.to/HN-SBR/itunes - YouTube: https://smevn.lnk.to/HN-SBR/youtube - YouTube Music: https://smevn.lnk.to/HN-SBR/youtubemusic - TikTok: https://smevn.lnk.to/HN-SBR/tiktok - Nhaccuatui: https://smevn.lnk.to/HN-SBR/nct - Zing MP3: https://smevn.lnk.to/HN-SBR/zingmp3 HELL NO | Official Music Video Music Production Singer & Composer: Saabirose Producers: Kado, Saabirose Mixing & Mastering: D.A Recorder: Đỗ Cẩm Khang Director: Romain Khanh Co-Director: Luu Anh Creative Director: Võ Ngọc Thuỵ Vân 1st Assistant Director: Thức (Antiantiart) Director of Photography: Trunduc (Antiantiart) Production House: Antiantiart & P92 Executive Producer: An Khang (Antiantiart) Executive Producer: Tuan Hô (P92 & Paume.) Producer: Giovi Phùng (Antiantiart) Line Producer: Anh Quốc (Antiantiart), Đinh Ngọc Anh Production Assistant: Tiến Đạt, Chung Nghĩa Location Manager: Hoàng Anh Art Department: Vidùa studio Art Director: Huệ Phương Art Assistant: Diệu Linh Set Decorators: Vũ Khôi Nguyên, Nguyễn Bá Ngọc, bùi hải an Stylist: Nekoh Stylist Assistant: Duhan Costume: Fanci, Lalune, Nekoh, Cailishyn, JAGA, Century, Outofsight, Elno Costume Designed by: Dang Viet Tung (Sequeen Dance Costome) Makeup Artist: Thuỷ Tiên Dance Producer: Xoăn Choreographer: 1metbontam Dancers: MADKIDZ Casts: Bii, Lưu Sơn, Quang Sơn, Công Minh, Nhật Vượng Camera & Lighting Equipment: CineHanoi Camera Operator: Phú Long Gaffer: Ngô Bá Trung (CineHanoi) Assistant Camera: Lê Văn Quỳnh, Nguyễn Văn Huy (CineHanoi) Lighting-Grip: Ngô Bá Dũng, Quách Văn Hiếu, Trần Công Phả DIT: Lương Thiên Lương Behind the Scene: Dzung Tran (Antiantiart) Post Production: Paume Post Producer: Tiffany Jacquier, Romain Algisi VFX Supervisor: Melchior Leroux VFX Artist: Kilian Pini 3D artist: Titouan Fourreau Editor: Eugène Signoret Assistant Editor: Maé Bragnier -------------------------------------- Theo dõi Saabirose tại: ► Đăng ký kênh tại đây: https://youtube.com/@Saabirose?si=okh8wo0K-t4EJJrt ► Facebook: https://www.facebook.com/saa2322 ► Fanpage: https://www.facebook.com/SaaSaaOfficial/ ► Instagram: https://www.instagram.com/saabirose22__/ ► Tiktok: www.tiktok.com/@saabirose22 --------------------- © Bản quyền thuộc về Saabirose © Copyright by Saabirose ☞ Do not reup

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0:16

Oh Hell No

Pushing Daisies - Emerson Cod Oh Hell No

published: 07 Apr 2009

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Oh Hell No

Oh Hell No

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Pushing Daisies - Emerson Cod Oh Hell No

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3:23

HELL NO: The Sensible Horror Film

Imagine a realm where the most horrifying terrors of the underworld emerge to wreak bloody...

published: 15 Oct 2013

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HELL NO: The Sensible Horror Film

HELL NO: The Sensible Horror Film

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Imagine a realm where the most horrifying terrors of the underworld emerge to wreak bloody vengeance upon any who... hmm? what's that? you wanna go literally anywhere else? yeah, good idea let's get out of here Directed by Joe Nicolosi Written by Joe Nicolosi and John Freiler Produced by Stephanie Noone Exe. Produced by Arts + Labor Director of Photography: Drew Daniels Music by Danny Gray Visual Effects by Moontower VFX, Ray Pena and Greg Omelchuck Cast: Alex Dobrenko, Ashley Spillers, Jessie Tilton, Sam Davis, Brandon Potter, Sam Eidson, Katie Folger, Sam Van Metre, Deke Garner, Jonny Mars, Zack Carlson, Bryan Connolly, David Hess, Mike Gassaway, Jason Newman, Elise Garza, April Swartz, Isaac Solomon, Marc Calderaro, Matt Van Doren, Drew Daniels, Aimee Thomas, Brock England, Jenniemarie Jemison, Clay Crenshaw, Andrew Matthews, Katie Graham, Will Elliott, Mallory Culbert, Joey Hood Assistant Director: Thomas Fernandes Gaffer: Emmett Kerr-Perkinson Art Department: April Swartz, Elise Garza, Stephanie Noone Assistant Camera: Zach Sprague Key Grip: Matt Van Doren Sound Recordist: Landry Gideon Sound Designer: Eric Friend Colorist / Online Editor: Daniel Stuyck Special Thanks: Kate Eads, Erik Horn, Derek Gildersleeve, Willie Rockefeller, Alan Berg, Zach Loeb, Derrick & Shareina Garner, Clay Liford, Bradley Jackson, Dave Ward, Kayla Kromer, Tony Brummer, Andy Young ,Don Swanos, Owen Egerton, Kirk Johnson, Peter Dealbert, Isaac Solomon, Sarah Siegel, Thomas Humphreys, Zilker Park Boat Rentals Great Hall Games, Quonset Hut, Delta Millworks

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3:02

Hell No - Gabriel Iglesias

Happy Throwback Thursday

published: 21 Jul 2022

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Hell No - Gabriel Iglesias

Hell No - Gabriel Iglesias

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Happy Throwback Thursday

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0:19

hell naw

did you eat a treat? @marks.gallery

published: 26 Jan 2024

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hell naw

hell naw

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did you eat a treat? @marks.gallery

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19:44

Hell NO❌⚠️

published: 01 Oct 2024

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Hell NO❌⚠️

Hell NO❌⚠️

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2:32

バカレア組 HELL,NO

published: 26 Mar 2013

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バカレア組 HELL,NO

バカレア組 HELL,NO

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'); } else { var query = elem.find('.keywords').html(); $.ajax({ context: elem, url: 'https://wn.com/api/upge/cheetah-search-adv/video', cache: true, data: { 'query': query }, dataType: 'jsonp', success: function(text) { if (text.length > 0) { video_id = text[0].id; elem.find('.player').html('

'); } } }); } } var stopAllYouTubeVideos = function() { var iframes = document.querySelectorAll('iframe'); Array.prototype.forEach.call(iframes, function(iframe) { iframe.contentWindow.postMessage(JSON.stringify({ event: 'command', func: 'pauseVideo' }), '*'); }); } jQuery(function() { jQuery(".playVideo").live("click", function() { if(!$(this).hasClass("played")){ stopAllYouTubeVideos(); var elem = $(this); setTimeout(function(){ mouseOverMe(elem); }, 1000); } }); jQuery(".description_box .expandContent").live("click", function() { elem = $(this).parent().parent().parent().find('.descContent'); if(elem.height() > 51) { elem.css('height', '44px'); $(this).html('Show More '); }else{ elem.css('height', 'auto'); $(this).html('Hide '); } }); jQuery('.interview-play-off').click(function() { $(".interview-play-off").hide(); $(".interview-play").show(); $(".videoplayer-control-pause").click(); }); jQuery(".video-desc .show_author_videos").live("click", function() { query = $(this).attr('title'); container = $(this).parent().parent().parent().find('.video-author-thumbs'); $(this).parent().parent().parent().find('.video-author-thumbs').css('height', '220px'); jQuery.ajax({ url: '/api/upge/cheetah-photo-search/videoresults', data: {'query': query}, success: function(text) { if(!text) { text = i18n("No results"); } container.html(jQuery(text)); } }); }); }); // -->

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Angie Velasco - HELL NO feat. Nico Valdi (Video Of...

Spice - Hell No (Official Audio)...

Team Hell No's 5 greatest moments...

SAABIROSE - HELL NO (prod. by KADO) | OFFICIAL MUS...

Oh Hell No...

HELL NO: The Sensible Horror Film...

Hell No - Gabriel Iglesias...

hell naw...

Hell NO❌⚠️...

バカレア組 HELL,NO...

• Hell No

  by Bargain Music
• Hell No

  by Better Than Ezra
• Hell No

  by Amanda Perez
• Hell No

  by Public Enemy
• Hell No

  by Ricki-lee
• Hell No

  by Sondre Lerche
• Hell No

  by All Saints
• Hell No

  by Memphis Bleek
• Hell No

  by Melanie B (Melanie Brown)
• Hell No

  by Cledus T. Judd
• Hell No

  by Frankee
• Hell No

  by Bruce Dickinson
• Hell No

  by Melanie B
• Hell No

  by Kat-tun
• Hell No

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• Hell No

  by Mel B

Hell No

by: Bargain Music

I was driving east from reno
Know that I was denver bound
So I stopped off in selena
Wanted to take a look around
I had zachary sitting next to me in the driver seat
Said damn this world is beat
Pull off here
He said no man this place here looks sketchy
This place was cool it was called cheetahs
They had bushnells they had brauts
Served me nachos with velveeta
How can I tell you man I was shocked
Give a little stretch and turned to survey around the room
Hey bartender how about round three haha
This ones on me
I had to adjust my eyes in the dim light
And I turned to my surprise this straight redneck looking girl said
Hey man do you mind if I sit here
Well I said hell no take off a load
She had blue jeans cut so damn low
Zach said hey she's yours josho
I said darling how long have you lived here
Ah shucks
When I looked across the bar
Seen fellas not feeling so right
Figured she probably slept with most guys in this dive
That don't matter it's just one night
Then I said whoa when she asked me to dance
And she smiled so devishly
I only said yes cause the jukebox was playing Hank Green
We were moving for a little bit
The next song was sung by travis tritt
And I said shit man alright that's it
It's time for another drink
What do you think darling
Sure
Alright
Serve em up son
Well the night was getting spendy
Already 75 dollars deep
She said excuse me baby I gotta go to the restroom
I'll meet you back at the bar
And I thought well shit man I gotta go to
But I didn't know she wasn't a lady
I didn't know she was a man
I didn't know until she was standing just like I was in the can
But I should have known
Hey dog
Ya beto