Light verb constructions (LVCs), such as "make a call" in English, can be said to be complex predicates in which the verb plays only a functional role. LVCs pose challenges for natural language understanding, as their semantics differ from usual predicate structures. We extend the existing corpus-based measures for identifying LVCs between verb-object pairs in English, by proposing using new features that use mutual information and assess other syntactic properties. Our work also incorporates both existing and new LVC features into a machine learning approach. We experimentally show that using the proposed framework incorporating all features outperforms previous work by 17%. As machine learning techniques model the trends found in training data, we believe the proposed LVC detection framework and statistical features is easily extendable to other languages.
REF applied machine learning techniques to extract LVCs.
Extending Corpus-Based Identification Of Light Verb Constructions Using A Supervised Learning Framework
Workshop On Multi-Word-Expressions In A Multilingual Context
Computer Science