In-depth Exploitation of Noun and Verb Semantics to Identify Causation in Verb-Noun Pairs
Mehwish Riaz, Roxana Gîrju · 2014
Recognition of causality is important to achieve natural language discourse under-standing. Previous approaches rely on shallow linguistic features. In this work, we propose to identify causality in verb-noun pairs by exploiting deeper seman-tics of nouns and verbs. Particularly, we acquire and employ three novel types of knowledge: (1) semantic classes of nouns with a high and low tendency to encode causality along with information regard-ing metonymies, (2) data-driven seman-tic classes of verbal events with the least tendency to encode causality, and (3) ten-dencies of verb frames to encode causal-ity. Using these knowledge sources, we achieve around 15 % improvement in F-score over a supervised classifier trained using linguistic features. 1