PPT-Modeling Semantic Relations Expressed by Prepositions

Vivek Srikumar and Dan Roth University of Illinois UrbanaChampaign Prepositions trigger relations John enjoyed the visit to the zoo in NYC E njoy Agent Enjoyer John Cause Thingenjoyed. Analysis. . . Kai-Wei Chang. Joint work with. . Scott Wen-tau . Yih, Chris Meek. Microsoft Research. Natural Language Understanding. Build an intelligent system that can interact with human using natural language. １２月７日. 研究会. 祭都援炉. (. マットエンロ. ). Up until now: Getting to know NLP. “Speech and Language Processing” (. Jurafsky. & Martin). 論文：. On-Demand Information Extract . Analysis. . for Lexical Semantics . and . Knowledge Base Embedding. UIUC 2014 . Scott Wen-tau . Yih. Joint work with. Kai-Wei . Chang, Bishan Yang, . Chris Meek, Geoff Zweig, John Platt. Microsoft Research. Children do not proceed as rapidly to two-word utterances as one . might expect.. Children . must first become aware that adding more . words will . improve communication,. Example: . ‘tummy . hurt’ is more effective than . S. imilarity to Semantic Relations. Georgeta. . Bordea. , November 25. Based on a talk by Alessandro . Lenci. . titled “Will DS ever become Semantic?”, Jan 2014. Distributional Semantics . (DS. Bryan Rink. University of Texas at Dallas. December 13, 2013. Outline. Introduction. Supervised relation identification. Unsupervised relation discovery. Proposed work. Conclusions. Motivation. We think about our world in terms of:. Analysis. . for Lexical Semantics . and . Knowledge Base Embedding. UIUC 2014 . Scott Wen-tau . Yih. Joint work with. Kai-Wei . Chang, Bishan Yang, . Chris Meek, Geoff Zweig, John Platt. Microsoft Research. Analysis. . . Kai-Wei Chang. Joint work with. . Scott Wen-tau . Yih, Chris Meek. Microsoft Research. Natural Language Understanding. Build an intelligent system that can interact with human using natural language. These slides illustrate things that different authors have . written using prepositions.. The illustrator takes the author’s words and then carefully tries to show them in a picture. . When you write a story you have to do it the other way round! – you have to imagine the picture in your head, and then carefully choose the right words to describe the picture.. Tom . Schimoler. Applications of NLP in determining Tag Redundancy in . Folksonomies. Big Question:. What is redundancy?. Although I have previously demonstrated examples of redundancy in tag clouds, there must be a . A word that shows . the relationship . between a. noun or a pronoun . and another word in the . sentence.. It is a word of “. position. ”.. Your math book is . underneath. the apple.. The preposition . Analysis. . . Kai-Wei Chang. Joint work with. . Scott Wen-tau . Yih, Chris Meek. Microsoft Research. Natural Language Understanding. Build an intelligent system that can interact with human using natural language. Prof. Dr. Ralf Möller. Universität zu Lübeck. Institut für Informationssysteme. Tanya Braun (Übungen). Acknowledgements. Slides by: Scott . Wen-tau . Yih. Describing joint work of Scott Wen-tau . You-shan Chung and Keh-Jiann Chen Abstract In this project we have studied Chinese noun-noun compounds NNCs and have found that N1 and N2 are linked either by semantic roles assigned by events complex