A Feature Structure Approach for Disambiguating Preposition Senses

Word Sense Disambiguation (WSD) continues to be an open research problem in spite of recent advances in the NLP field, especially in machine learning. WSD for open-class words is well understood. However, WSD for closed class structural words (such as prepositions) is not so well resolved, and their role in frame semantics seems to be a relatively unknown area. This research uses a new method to disambiguate preposition senses by using a combined lookup from FrameNet and TPP databases. Motivated by recent work by Popescu, Tonelli, & Pianta (2007), it extends the concept to provide a deterministic WSD of prepositions using the lexical information drawn from the sentences in a local context. While the primary goal of the research is to disambiguate preposition sense, the approach also assigns frames and roles to different sentence elements. The use of prepositions for frame and role assignment seems to be a largely unexplored area which could provide a new dimension to research in lexical semantics