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Shallow versus deep syntactic dependencies for relation extraction tasks

The aim of this project is to evaluate three systems of syntactic dependency representation for English, differing in terms of the relative "depth" of the underlying linguistic analyses, based on how effective each representation format is as the input into typical relation extraction tasks.

Syntactic dependency representation systems

Recent years have seen growing research interest in syntactic parsers which output, not labelled bracketings corresponding to syntactic phrase structure trees, but rather sets of labelled dependencies between heads and dependents. It has been argued that parser output based on syntactic dependencies is a better option for two main reasons: (a) this format is more theory-neutral, allowing a more level playing field for parser evaluation; and (b) syntactic dependencies are more appropriate for information extraction tasks than labelled bracketings.

A number of different systems of syntactic dependency representation have been proposed for English, which can be seen as varying according to the "depth" of the linguistic analyses they presuppose.

The most basic, "shallowest" systems assume that the syntactic representation of a sentence constitutes a TREE - in other words EVERY word (apart from that which functions as the "root") is a dependent of exactly ONE other word. (e.g. Link parser, Minipar, CoNLL shared tasks 2006-2008).

Three distinct syntactic dependency representation systems will be evaluated:

  • CoNLL dependencies (unordered trees)
  • Stanford typed dependencies (limited reentrancy)
  • Deep syntactic roles (full reentrancy and normalisation)

Relation extraction tasks

Three distinct relation extraction tasks will be undertaken, from three contrasting domains:

  • biomedical - protein-protein interactions and tissue expressions in the ITI TXM corpora
  • educational - some relation extraction task using the Beetle corpus?
  • cultural heritage - some relation extraction task using Kate Byrne's corpus?

-- MarkMcConville - 12 Aug 2008

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Topic revision: r1 - 12 Aug 2008 - 15:01:17 - MarkMcConville
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