Behavior Research Methods, Instruments, Computers

this article, we describe our efforts in using state-of-the-art natural language analysis technolo113 Copyright 2004 Psychonomic Society, Inc. This work was supported by a grant from the National Science Foundation Linguistic Program to B. M.Thanks to ChristopheParisse for creating the POST program and to Yuriko Oshima-Takane and her students at McGill for producing these disambiguated tags for the training of POST. Maria Lamendola assisted with hand-checking of the results of LCFlex. Correspondenceconcerning this article should be addressed to K. Sagae, LanguageTechnologies Institute, Carnegie Mellon University, 5000Forbes Avenue, Pittsburgh,PA 15213 (e-mail: sagae@cs.cmu.edu). Automatic parsing of parental verbal input KENJI SAGAE, BRIAN MACWHINNEY, and ALON LAVIE Carnegie Mellon University, Pittsburgh, Pennsylvania To evaluate theoretical proposals regarding the course of child language acquisition, researchers often need to rely on the processing of largenumbers of syntacticallyparsed utterances,both from children and from their parents. Because it is so difficult to do this by hand, there are currently no parsed corpora of child language input data. To automate this process, we developed a system that combined the MOR tagger, a rule-based parser, and statistical disambiguation techniques. The resultant system obtained nearly 80% correct parses for the sentences spoken to children. To achieve this level, we had to construct a particular processing sequence that minimizes problems caused by the coverage/ ambiguity tradeoff in parser design. These procedures are particularly appropriate for use with the CHILDES database, an international corpus of transcripts. The data and programs are now freely available over the Internet

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