WeSearch_LexicalFiltering

Background

Working with a lattice of lexical hypotheses and an (über)tagger, we seek to develop a filtering function that discards unlikely hypotheses. The formalisation of the lexical filtering process may be found [http://dl.dropbox.com/u/680530/WeSearch/Lexical%20Filtering/formalisation.pdf here].

TNT output for filtering of LE types

One such filter function maps PTB tags output from the TNT tagger onto LE Types. Mappings may be derived intuitively from inspection of a [http://dl.dropbox.com/u/680530/WeSearch/Lexical%20Filtering/tnt.le.confusion.pdf confusion matrix] detailing the choices of TNT with respect to LE types.

An alternative approach is to programmatically find mappings based on the preferred outcomes of lexical filtering, (i.e. gains in parser efficiency versus losses in parser accuracy and coverage). These outcomes may be approximated by examining the relations between TNT precision, TNT recall and the lexical ambiguity of LE types.

TODO: Parser efficiency is best approximated by parse forests instead of the selected best parse.

Related Work

• Rebecca Driden (2009), [http://www.dridan.com/research/papers/dridan-phdthesis.pdf Using Lexical Statistics to Improve HPSG Parsing], PhD Thesis, Saarland University