Abstract
We present a linguistically-motivated technique for the recognition and grouping of simplex noun phrases (SNPs) called LinkIT. Our system has two key features: (1) we efficiently gather minimal NPs, i. e. SNPs, as precisely and linguistically defined and motivated in our paper; (2) we apply a refined set of post-processing rules to these SNPs to link them within a document. The identification of SNPs is performed using a finite state machine compiled from a regular expression grammar, and the process of ranking the candidate significant topics uses frequency information that is gathered in a single pass through the document. We evaluated the NP identification component of LinkIT and found that it outperformed other NP chunkers in precision and recall. The system is currently used in several applications which are described, such as web page characterization and multi-document summarization.
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