Paper: Shallow Parsing On The Basis Of Words Only: A Case Study

ACL ID P02-1055
Title Shallow Parsing On The Basis Of Words Only: A Case Study
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2002
Authors

We describe a case study in which a memory-based learning algorithm is trained to simultaneously chunk sentences and assign grammatical function tags to these chunks. We compare the algo- rithm’s performance on this parsing task with varying training set sizes (yielding learning curves) and different input repre- sentations. In particular we compare in- put consisting of words only, a variant that includes word form information for low- frequency words, gold-standard POS only, and combinations of these. The word- based shallow parser displays an appar- ently log-linear increase in performance, and surpasses the flatter POS-based curve at about 50,000 sentences of training data. The low-frequency variant performs even better, and the combinations is best. Com- parative experiments with a ...