ML for NLP: Ling 572

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ML for NLP Ling 572

• Achim Ruopp
• Zhengbo Zhou
• Albert Bertram

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Outline

• Tagging Introduction
• Blah, blah, blah, you did this too
• And now for something possibly different
• Results
• Comments
• Questions
• Snide remarks

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Tagging introduction

• Tagging is pretty simple
• Relatively good results tagging with
• Tag argmax p(t word )
• t in Tagset
• The problem is well understood
• Algorithm changes can be clearly visible

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Preaching to the Choir

• You all did this too
• P1 HMM/FST trigram tagger
• P2 TBL tagger
• P3 Maximum Entropy tagger

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Forking Processes

• Project 4 offered some choices
• Self-training FTW

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General Algorithm

• Initialize
• Tagged data T
• Untagged data U
• Loop
• Train a tagger M on T
• Use M to add tags to U, creating U
• Move the best sentences from U into T
• Replace U with the rest of U
• End when youre satisfied

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Experimental Details

• For i1,5
• Initialize T with i1000 sentences
• For j15,25,35
• Initialize U with j 1000 sentences
• Do self training
• Best of U is defined as the best n
• Where n 20 of T
• Satisfied when U 0

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Results (I) Graph
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Results (II) Zoomed in
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Results (III) Projects 1-3

• Probably not much new here
• You all did projects 1-3
• That outlier though TBL with simple unknown word
  treatment
• The simpler approach to unknown word handling has
  much worse results.

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Results (IV) Project 4

• Overall, more than 1 improvement
• Not spectacular
• Better than a poke in the eye with a sharp stick
• Probably works better in a domain with fewer
  degrees of freedom.
• Then again, unlabelled data is cheap
• wget r http//www.gutenberg.org/

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Further Considerations

• Not much to say about P1-3, but for P4
• We used a trigram tagger
• Higher probabilities for shorter sentences
• May want a quality measure rather than this
• Unknown words are problematic
• Try another tagger?

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Done Done Done

• Questions?
• Comments.
• Snide remarks.
• Chuck Norris jokes.

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For the Morbidly Curious
Project 1 tagging accuracy
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For the Morbidly Curious
Project 2 tagging accuracy
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For the Morbidly Curious
Project 3 tagging accuracy
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For the Morbidly Curious
Project 4 tagging accuracy/number of sentences
added