Automatic extraction of subcorpora based on subcategorization frames from a part-of-speech tagged corpus

Automatic extraction of subcorpora based on subcategorization frames from a part-of-speech tagged corpus Susanne GAHL UC Berkeley, Department of Linguistics ICSI 1947 Center St, Suite 600 Berkeley, CA 94704-1105 gahl@ icsi.berkeley.edu Abstract This paper presents a method for extracting sub.cor.pora documenting different subcate- gorlzatlon frames for verbs, nouns, and adjectives in the 100 mio. word British National Corpus. The extraction tool consists of a set of batch files for use with the Corpus Query Processor (CQP), which is part of the IMS corpus workbench (cf. Christ 1994a,b). A macroprocessor has been developed that allows the user to specify in a simple input file which subcorpora are to be created for a given lemma. The resulting subcorpora can be used (1) to provide evidence for the subcategorization properties of a given lemma, and to facilitate the selection of corpus lines for lexicographic research, and (2) to determine the frequencies of different syntactic contexts of each lemma. Introduction A number of resources are available for obtaining subcategorization information, i.e. information on the types of syntactic complements associated with valence-bearing predicators (which include verbs, nouns, and adjectives). This information, also referred to as valence information is available both in machine-readable form, as in the COMLEX database (Macleod et al. 1995), and in human- readable dictionaries (e.g. Hornby 1989, Procter 1978, Sinclair 1987). Increasingly, tools are also becoming available for acquiring subcategorization information from corpora, i.e. for inferring the subcategorization frames of a given lemma (e.g. Manning 1993). None of these resources provide immediate access to corpus evidence, nor do they provide information on the relative frequency of the patterns that are listed for a given lemma. There is a need for a tool that can (1) find evidence for subcategorization patterns and (2) determine their frequencies in large corpora: 1. Statistical approaches to NLP rely on information not just on the range of combinatory possibilities of words, but also the relative frequencies of the expected patterns. 2. Dictionaries that list subcategorization frames often list expected patterns, rather than actual ones. Lexicographers and lexicologist need access to the evidence for this information. 3. Frequency information has come to be the focus of much psycholinguistic research on sentence processing (see for example MacDonald 1997). While information on word frequency is readily available (e.g. Francis and Kucera (1982)), there is as yet no easy way of obtaining information from large corpora on the relative frequency of complemen- ration patterns. None of these points argue against the use- fulness of the available resources, but they show that there is a gap in the available in- formation. To address this need, we have developed a tool for extracting evidence for subcategorization patterns from the 100 mio. word British National Corpus (BNC). The tool is used as part of the lexicon-building process in the FrameNet project, an NSF-funded project aimed at creating a lexical database based on the principles of Frame Semantics (Fillmore 1982). 428 1 Infrastructure 1,1 Tools We are using the 100 mio. word British National Corpus, …

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