Data Management

Querying Linguistic Annotations

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Executive Summary

Over the past decade, a variety of expressive linguistic query languages have been developed. The most scalable of these have been implemented on top of an existing database engine. However, with the arrival of efficient, wide-coverage parsers, it is feasible to parse text on a scale that is several orders of magnitude larger. The authors show that the existing database approach will not scale up, and speculate on a new approach that leverages proximity search in the context of an IR engine. They also propose a simple syntax for querying linguistic annotations, avoiding the usability problems with existing tree query languages.

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