PPT-NLP Introduction to NLP Earley

Parser Earley parser Problems with left recursion in topdown parsing VP VP PP Background Developed by Jay Earley in 1970 No need to convert the grammar to CNF Left to right Complexity. Detecting Questions in Micro-text. Kyle Dent <. kdent@parc.com. >. Original Question: Do people use Twitter to ask questions?. First Answer: Of course.. But to what extent and what kinds of questions?. Morphology and the Lexicon. Mental Lexicon. What is the meaning of cat? Its pronunciation? Part of speech?. What is the meaning of . wug. ?. What is the meaning of . cluvious. ?. Compare . traftful. and . Parsing with CFGs. CMSC 723: Computational Linguistics I ― Session #7. Jimmy Lin. The . iSchool. University of Maryland. Wednesday, October 14, 2009. Today’s Agenda. Words… . structure…. meaning…. the almighty……….. . NLP. . DR.Eman. . Diab. introduction. introduction. The word . Neuro. linguistic programming can be broken down to three distinct words: . Semantic Role Labeling. Syntactic Variation. Last week, Min broke the window with a hammer.. The window was broken with a hammer by Min last week. With a hammer, Min broke the window last week. Last week, the window was broken by Min with a hammer. Subproblems. . Meliha. . Yetisgen-Yildiz. From last week’s discussion. Presentation. Schedule. : . http. ://faculty.washington.edu/melihay/. MEBI591C.htm. 50 . minutes . presentation+discussion+question. Language Annotation, Modeling, and Processing . Toolkit (CLAMP) . Hua Xu. School of Biomedical Informatics, . University . of Texas Health Science Center at Houston . 1. The Transportability Problem of . Properties of Propositional Logic. Pros. Compositional. Declarative. Cons. Limited expressive power. Represents facts. First Order Logic. Used to represent. Objects – Martin the cat. Relations – Martin and Moses are brothers. Categorial. Grammar (CCG). Combinatory Categorial Grammar (CCG). Complex types. E.g., . X/Y. and . X\Y. These take an argument of type . Y. and return an object of type . X. . . X/Y – means that Y should appear on the right. Jimmy Lin. The . iSchool. University of Maryland. Wednesday, September 2, 2009. NLP. IR. About Me. Teaching Assistant: . Melissa Egan. CLIP. About You (pre-requisites). Must be interested in NLP. Must have strong computational background. Semantic Parsing. Converting natural language to a logical form. e.g., executable code for a specific application. Example:. Airline reservations. Geographical query systems. Stages of Semantic . Parsing. Dan Jurafsky. Stanford University. Spring 2020 . Introduction and Course Overview. Thanks to . Tsvetkov. and Black course . for ideas and slides!. How should we use NLP for good and not for bad?. The common misconception is that language has to do with . by Hua Xu. Recent Activities. ETL tool development. Note Type Normalization. COVID-19 lab test normalization . A Potential ETL Workflow for NLP. Note. Note_NLP. Measure-. ment. Condition. Procedure. Drug. Smoothing. If the vocabulary size is |V|=1M. Too many parameters to estimate even a unigram model. MLE assigns values of 0 to unseen (yet not impossible) data. Let alone bigram or trigram models. Smoothing (regularization).