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As natural language processing (NLP) algorithms become ever more
successful, methods are needed for conveniently re-using their results,
both for additional processing, and for end applications such as
text mining and information retrieval. We have developed
the Layered Query Language (LQL) and a system
architecture that supports queries over layers of annotation on
natural language text. The model allows for both hierarchical and
overlapping layers and for querying at multiple levels of
description. The implementation is built on top of a standard RDBMS,
and, by using carefully constructed indexes, can execute complex
queries over very large collections.
More information:
(The demo is no longer active.)
Two short papers on the system and LQL:
Supporting Annotation Layers for Natural Language Processing,
Preslav Nakov, Ariel Schwartz, Brian Wolf, and Marti Hearst,
in
ACL 2005 Poster/Demo Track
pdf
Scaling Up BioNLP:
Application of a Text Annotation Architecture to Noun Compound Bracketing,
Preslav Nakov, Ariel Schwartz, Brian Wolf, and Marti Hearst,
in ACL/ISMB BioLINK SIG 2005
pdf
This research is supported by NSF grant DBI-0317510 as well as
a gift from Genentech, an NSF ITR grant
(EIA-0122599, part of the CITRIS
project), and was previously supported by an ARDA
AQUAINT contract.
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