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Semantics: Semantic Grammar & Information Extraction

Semantics: Semantic Grammar & Information Extraction

Semantics: Semantic Grammar & Information Extraction. CMSC 35100 Natural Language Processing May 13, 2003. Potential Projects. Develop a morphological transducer for a portion of a language of your choice

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381 views • 20 slides
Semantics: Semantic Grammar & Information Extraction

Semantics: Semantic Grammar & Information Extraction

Semantics: Semantic Grammar & Information Extraction. CMSC 35100 Natural Language Processing May 13, 2003. Potential Projects. Develop a morphological transducer for a portion of a language of your choice

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207 views • 20 slides
Semantic Analysis

Semantic Analysis

Semantic Analysis. CMSC 35100 Natural Language Processing May 8, 2003. Roadmap. Semantic Analysis Motivation: Understanding commands Approach I: Syntax-driven semantic analysis Augment productions with semantic component Lambda calculus formulation Approach II: Semantic Grammar

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576 views • 16 slides
Semantic Analysis

Semantic Analysis

Semantic Analysis. CMSC 35100 Natural Language Processing May 8, 2003. Roadmap. Semantic Analysis Motivation: Understanding commands Approach I: Syntax-driven semantic analysis Augment productions with semantic component Lambda calculus formulation Approach II: Semantic Grammar

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179 views • 16 slides
Natural Language Processing

Natural Language Processing

Natural Language Processing. Chapter 15 (part 2). Harder Example. What makes this hard? What role does Harry play in all this?. Example in class: John told Mary to Walk Fido. Non-Compositionality.

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229 views • 15 slides
Synchronous Tree-Adjoining Grammars

Synchronous Tree-Adjoining Grammars

Synchronous Tree-Adjoining Grammars. Authors: Stuart M. Shieber and Yves Schabes Reporter: ??? Professor: ???. Introduction. Advantage of TAG (Tree-adjoining grammar) The domain of locality The statements of dependencies and recursion possibilities in a tree are factored Synchronous TAGs

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328 views • 15 slides
Natural Language Processing

Natural Language Processing

Natural Language Processing. Lecture Notes 12 Chapter 15 (part 2). Harder Example. What makes this hard? What role does Harry play in all this?. Example in class: John told Mary to Walk Fido. Non-Compositionality.

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160 views • 15 slides

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