Paper: NER Systems That Suit User's Preferences: Adjusting The Recall-Precision Trade-Off For Entity Extraction

ACL ID N06-2024
Title NER Systems That Suit User's Preferences: Adjusting The Recall-Precision Trade-Off For Entity Extraction
Venue Human Language Technologies
Session Short Paper
Year 2006
Authors

We describe a method based on “tweak- ing” an existing learned sequential classi- fier to change the recall-precision tradeoff, guided by a user-provided performance criterion. This method is evaluated on the task of recognizing personal names in email and newswire text, and proves to be both simple and effective.