October 30, 1998

Ken Barker
School of Information Technology and Engineering
University of Ottawa

Identifying Semantic Relationships in Complex Noun Phrases

Complex noun phrases carry much of the information in English texts. Unfortunately for systems that want to get at that information, there are few surface indicators of the underlying meaning of a noun phrase. Such systems must compensate for the lack of clues with other information. One way is to load the system with lexical semantics for nouns and adjectives. This merely shifts the problem elsewhere: how do we define the lexical semantics and build large semantic lexicons? Another way is to find constructions similar to a given noun phrase, for which the semantic relationships among components are already known.

In this talk I will present a semi-automatic system that identifies semantic relationships in noun phrases without using precoded noun or adjective semantics. Instead, partial matching on similar, previously analyzed noun phrases leads to a tentative interpretation of a new input, which is accepted or corrected by a cooperative user. I will break the bad news: similarity is not easily assessed, similar analyzed constructions may not exist, and if they do exist, their analyses may not be appropriate for the current phrase. I will also share the good news: processing can start with no prior analyses, and as more noun phrases are analyzed, the system learns to find better interpretations and reduces its reliance on the user.

This talk contains no sliding boxes.

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