Semantic memory for syntactic disambiguation


In this paper we address a type of verb-phrase ambiguity that has proven problematic for syntactic parsers. We discuss the ambiguity from a linguistic theory perspective and explain how we carried out a corpus analysis task using widely consulted databases to find examples and quantify the extent of the problem. We then sketch how we were able to encode the associated knowledge in the agent's semantic memory to provide a resolution when examples like those from the corpus were encountered. When such prior experience cannot be brought to bear, we mention how the system uses a semantic similarity measure to resolve the ambiguity, and then stores the result in semantic memory for future access. We conclude with some results, remarks about performance, and future related work.

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