Linguistic Annotation for Valence Acquisition and for its Evaluation

Abstract

Valence acquisition is the task consisting in the automatic extraction (learning) of subcategorisation – or argument structure – from corpora. In this talk I will concentrate on two issues. The first issue is: how much linguistic annotation do we need for valence acquisition? Approaches range from linguistically lean, e.g., Brent’s 1993 proposal to infer valence information from co-ocurrences of verbs with pronouns and functional words, to more recent proposals to read valence off from lavishly annotated treebanks. I will present the results of some experiments from Polish suggesting that shallow (or partial) parsing may be as useful in this task as more difficult and less efficient deep parsing. The second issue concerns the evaluation of the results of automatic valence acquisition. The common methodology is to compare the automatic results to a manually constructed valence dictionary, but – again on the basis of some experiments carried out for Polish – I will point out various weaknesses of this methodology and argue for the more costly and, hence, less common corpus-based evaluation.