Some Advances in Transformation-Based Part of Speech Tagging

Computer Science – Computation and Language

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

6 Pages. Code available

Scientific paper

Most recent research in trainable part of speech taggers has explored stochastic tagging. While these taggers obtain high accuracy, linguistic information is captured indirectly, typically in tens of thousands of lexical and contextual probabilities. In [Brill92], a trainable rule-based tagger was described that obtained performance comparable to that of stochastic taggers, but captured relevant linguistic information in a small number of simple non-stochastic rules. In this paper, we describe a number of extensions to this rule-based tagger. First, we describe a method for expressing lexical relations in tagging that are not captured by stochastic taggers. Next, we show a rule-based approach to tagging unknown words. Finally, we show how the tagger can be extended into a k-best tagger, where multiple tags can be assigned to words in some cases of uncertainty.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Some Advances in Transformation-Based Part of Speech Tagging does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Some Advances in Transformation-Based Part of Speech Tagging, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Some Advances in Transformation-Based Part of Speech Tagging will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-39351

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.