I256: Applied Natural Language Processing

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I256 Applied Natural Language Processing
Marti Hearst Sept 25, 2006    
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Shallow Parsing

• Break text up into non-overlapping contiguous
  subsets of tokens.
• Also called chunking, partial parsing, light
  parsing.
• What is it useful for?
• Entity recognition
• people, locations, organizations
• Studying linguistic patterns
• gave NP
• gave up NP in NP
• gave NP NP
• gave NP to NP
• Can ignore complex structure when not relevant

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A Relationship between Segmenting and Labeling

• Tokenization segments the text
• Tagging labels the text
• Shallow parsing does both simultaneously.

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Chunking vs. Full Syntactic Parsing

• G.K. Chesterton, author of The Man who was
  Thursday

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Representations for Chunks

• IOB tags
• Inside, outside, and begin
• Why do we need a begin tag?

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Representations for Chunks

• Trees
• Chunk structure is a two-level tree that spans
  the entire text, containing both chunks and
  non-chunks

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CONLL Collection

• From the Conference on Natural Language Learning
  Competition from 2000
• Goal create machine learning methods to improve
  on the chunking task

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CONLL Collection

• Data in IOB format from WSJ
• Word POS-tag IOB-tag
• Training set 8936 sentences
• Test set 2012 sentences
• Tags from the Brill tagger
• Penn Treebank Tags
• Evaluation measure F-score
• 2precisionrecall / (recallprecision)
• Baseline was select the chunk tag that is most
  frequently associated with the POS tag, F 77.07
• Best score in the contest was F94.13

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nltk_lite and CONLL2000
Note that raw hides the IOB format
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nltk_lite and CONLL2000
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nltk_lite and CONLL2000
pp() stands for pretty print and applies to the
Tree data structure.
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nltk_lite chunks in treebank
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nltk_lite parses in treebank
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Chunking with Regular Expressions

• This time we write regexs over TAGS rather than
  words
• ltDTgtltJJgt?ltNNgt
• ltNN.gt
• ltJJNNgt
• Compile them with parse.ChunkRule()
• rule parse.ChunkRule(ltDTNNgt)
• chunkparser parse.RegexpChunk(rule,
  chunk_node NP)
• Resulting object is of type Tree
• Top-level node called S
• Can change this label if you want, in third
  argument to RegexpChunk

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Chunking with Regular Expressions
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Chunking with Regular Expressions

• Rule application is sensitive to order

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Chinking

• Specify what does not go into a chunk.
• Kind of like specifying punctuation as being not
  alphanumeric and spaces.
• Can be more difficult to think about.

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Practice Regexp Chunking

• Write rules to be able to produce this kind of
  chunking

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Next Time

• Evaluating Shallow Parsing
• Begin Text Summarization