Material Detail

This video was recorded at 15th International Multiconference on Information Society, Ljubljana 2012. 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.

Disciplines:

• Science and Technology  / Computer Science