Project Presentation

1
Project Presentation
Lin572 Advanced Statistic Methods in NLP

• Team Members
• Anna Tinnemore
• Gabriel Neer
• Yow-Ren Chiang

2
PART 3

• MaxEnt
• (yipee!)

3
The Good Stuff

• Simple feature templates and extraction
• Elegant data structures for storage and easy
  access
• Pretty good results!

4
The Bad Stuff

• Hmmm. . . .

5
Features

• A few short loops collected the most relevant
  context features
• No long-winded feature templates
• Easy-access hashes

6
Decent Results

• Mid-nineties increasing with the size of the
  training data
• Result

7
PART 4

• Task 2
• Bagging

8
Tie Function

• use TieFile
• use Fcntl
• for my bag_num (1 .. B)
• The Nth bag from file foo.txt becomes
  foo.txtbagN, etc.
• my bag_name "file_name-bagbag_num"
• open (BAG, "gtbag_name")
• or die "Can't open bag_name for writing !"
• for (_at_lines)
• Pick random line of file.
• my line lines rand _at_lines
• print BAG "line\n" Output to the bag.

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Combination

• VOTING!!

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Step 1

• Loop through file and remember words. Keep them
  grouped by sentence.
• while (ltFILEgt)
• foreach (_at_word_tags)
• my _at_wordtag split /\//
• push (_at_words, (wordtag0))
• push (_at_sentences, (\_at_words))

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Step 2

• Go through file and for each word, increase the
  count of its tag
• for (_at_ARGV)
• my tag_index 0
• while (ltFILEgt)
• foreach (_at_word_tags)
• my _at_wordtag split /\//
• my tag wordtag1
• tagstag_index-gttag
• tag_index

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Step 3

• Go through the sentences and print out each
  word/tag pair.
• my tag_index 0
• foreach my sent (_at_sentences)
• foreach my word (_at_sent)
• my tag max_tag(tagstag_index)
  tag_index print "word/tag "
• print "\n"

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Finding the Best Tag

• Find the tag with the highest count.
• sub max_tag
• my tag_hash shift
• (my tag) keys tag_hash
• my tag_count tag_hash-gttag
• foreach (keys tag_hash)
• if (tag_hash-gt_ gt tag_count)
• tag _
• tag_count tag_hash-gttag
• return tag

14
Procedure

• Creating Bootstrap samples
• Treating the file as an array for lines.
• N random array indices are selected and each
  corresponding line is output to a file
• Combine_tool.pl
• opens the file corresponding to its first
  argument
• reads in all words, aggregated by sentence
• An array of tag hashes is created.
• For each file in its arg list, opens that file
  and reads the tags sequentially
• The hash item corresponding to the tag in the
  appropriate index of the tag area is incremented
• For each index, the hash label with the highest
  count is chosen as the correct tag
• Re-associate the tags with their words
• Print out the word/tag pairs

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Result