Genic Interaction Extraction with Semantic and Syntactic Chains
Sebastian Riedel
and
Ewan Klein
Abstract:
This paper describes the system that we submitted to the Learning Language in
Logic Challenge of extracting directed genic interactions from sentences in
Medline abstracts. The system uses Markov Logic, a framework that combines
log-linear models and First Order Logic, to create a set of weighted clauses
which can classify pairs of gene named entities as genic interactions. These
clauses are based on chains of syntactic and semantic relations in the parse or
Discourse Representation Structure (drs) of a sentence, respectively. Our
submitted results achieved 52.6% F-Measure on the dataset without and 54.3% on
the dataset with coreferences. After adding explicit clauses which model
non-interaction we were able to improve these numbers to 68.4% and 64.7%,
respectively.
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