Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web
Chikara Hashimoto, Kentaro Torisawa, Stijn De Saeger, Jong–Hoon Oh, Jun’ichi Kazama · 2012
We propose a new semantic orientation, Ex-citation, and its automatic acquisition method. Excitation is a semantic property of predicates that classifies them into excitatory, inhibitory and neutral. We show that Excitation is useful for extracting contradiction pairs (e.g., destroy cancer ⊥ develop cancer) and causality pairs (e.g., increase in crime ⇒ heighten anxiety). Our experiments show that with automatically acquired Excitation knowledge we can extract one million contradiction pairs and 500,000 causality pairs with about 70 % precision from a 600 million page Web corpus. Furthermore, by combining these extracted causality and contradiction pairs, we can generate one mil-lion plausible causality hypotheses that are not written in any single sentence in our corpus with reasonable precision. 1