Identifying Good Patterns for Relation Extraction
published: Nov. 16, 2012, recorded: October 2012, views: 84
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
In pattern based relation extraction, patterns that with high precision and recall produce semantically useful relations are preferred. We present a technique similar to n-gram extraction that extracts patterns from large text corpora and calculates statistics, like frequency, minimal token frequency and normalized expectation, which guide to preferred patterns. Patterns have named-instances and/or one variable length gap as arguments. We extracted patterns from a large news corpus and translated them to Cyc relations. We focused on four patterns, which we evaluate by asserting their translated relations to Cyc knowledge base.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !