Paper: SRL-Based Verb Selection for ESL

ACL ID D10-1104
Title SRL-Based Verb Selection for ESL
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010

In this paper we develop an approach to tackle the problem of verb selection for learners of English as a second language (ESL) by using features from the output of Semantic Role La- beling (SRL). Unlike existing approaches to verb selection that use local features such as n-grams, our approach exploits semantic fea- tures which explicitly model the usage context of the verb. The verb choice highly depends on its usage context which is not consistently captured by local features. We then combine these semantic features with other local fea- tures under the generalized perceptron learn- ing framework. Experiments on both in- domain and out-of-domain corpora show that our approach outperforms the baseline and achieves state-of-the-art performance.1