Lecture20-wsd - Thisworkislicensed under...

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1 CS 479, Section 1: Natural Language Processing Lecture #20: Word Sense Disambiguation Thanks to Dan Klein of UC Berkeley for many of the materials used in this lecture. This work is licensed under a Creative Commons Attribution Share Alike 3.0 Unported License . Announcements Project #2, Part 1 Early: Monday Due: Wednesday Questions? Mid term Exam Prepare your questions Review: Wed. in class Next week: Thu Sat No class on Friday Objectives Review the idea behind joint, generative models. Discuss the challenge of word sense disambiguation and approach it as a classification problem. Explore knowledge sources (“features”) that might help us do a better job of disambiguating word senses. Motivate the need for conditional models, trained discriminatively. Prepare to see maximum entropy training. Recently … Models for text categorization (Naïve Bayes, class conditional LMs) These are Joint / Generative models: Break complex structure down into derivation steps “factors” or “local models” Each step is a categorical choice (at least for our current purposes), conditioned on specified context Estimate those categorical distributions by collecting counts and smoothing Backbone of statistical NLP until very recently Today: motivating conditional maximum entropy, a Conditional model, trained discriminatively . c w 1 w 2 w n . . . START Word Senses Words have multiple distinct meanings, or senses: plant : living plant, manufacturing plant, … title : name of a work, ownership document, form of address, material at the start of a film, … Many levels of sense distinctions Homonymy: totally unrelated meanings (river bank, money bank) Polysemy: related meanings (star in sky, star on tv) Systematic polysemy: productive meaning extensions (organizations to their buildings) or metaphor Sense distinctions can be extremely subtle (or not) Granularity of senses needed depends a lot on the task Why is it important to model word senses?
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This note was uploaded on 10/18/2011 for the course CS 479 taught by Professor Ericringger during the Fall '11 term at BYU.

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Lecture20-wsd - Thisworkislicensed under...

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