Evaluating models of syntactic category acquisition without using a gold standard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A number of different measures have been proposed for evaluating computational models of human syntactic category acquisition.
They all rely on a gold standard set of manually determined
categories. However, children’s syntactic categories
change during language development, so evaluating against a
fixed and final set of adult categories is not appropriate. In this
paper, we propose a new measure, substitutable precision and
recall, based on the idea that words which occur in similar
syntactic environments share the same category. We use this
measure to evaluate three standard category acquisition models
(hierarchical clustering, frequent frames, Bayesian HMM)
and show that the results correlate well with those obtained
using two gold-standard-based measures.
Original languageEnglish
Title of host publicationProceedings of the 31st Annual Conference of the Cognitive Science Society
Publication statusPublished - 2009

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