PPT-NLP Introduction to NLP

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 . By Cindy Carless. 14 Nov 14. What a mouthful…. So much in fact that I thought I had bitten off more than I could chew…. Yet for “Tasting” . LetsTest. it seems very appropriate. Some appetisers to focus on. 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?. 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. Regina Barzilay. What is NLP?. Goal: intelligent processing of human language. Not just effective string matching. Applications of NLP technology:. Less ambitious (but practical goals): spelling corrections, name entity extraction. Class Logistics. Quiz. Where is this quote from?. Dave Bowman. : Open the pod bay doors, HAL.. HAL. : I’m sorry Dave. I’m afraid I can’t do that.. Quiz Answer. “2001: A Space Odyssey” . 1968 film by Stanley Kubrick . alebo prečo . som mal dávať väčší pozor na . slovenčine. Róbert . Móro. 26. .. 2. .201. 3. moro. @. fiit. .. stuba.sk. I made her duck.. I made her duck.. Uvaril (upiekol) som jej kačku.. Uvaril som kačku, ktorá jej patrí.. 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. -. Kasami. -Younger (CKY) Parsing. Notes on Left Recursion. Problematic for many parsing methods. Infinite loops when expanding. But appropriate linguistically. NP -> DT N. NP -> PN. DT -> NP ‘s. 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. Jiho . Han. Ronny (. Dowon. ) . Ko. Objective:. automatically generate the summary of review extracting the strength/weakness of the product. Use NLP techniques to predict ratings. Similar to sentimental analysis. 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 . 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).