Paper: Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection

ACL ID W10-3008
Title Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2010
Authors

Hedge cues were detected using a super- vised Conditional Random Field (CRF) classifier exploiting features from the RASP parser. The CRF’s predictions were filtered using known cues and unseen in- stances were removed, increasing preci- sionwhileretainingrecall. Rulesforscope detection, based on the grammatical re- lations of the sentence and the part-of- speech tag of the cue, were manually- developed. However, another supervised CRFclassifierwasusedtorefinethesepre- dictions. As a final step, scopes were con- structed from the classifier output using a small set of post-processing rules. Devel- opmentofthesystemrevealedanumberof issues with the annotation scheme adopted by the organisers.