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Seeing clearly: Frame Semantic, Psycholinguistic, and Cross ...

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CHAPTER 6. FUTURE RESEARCH DIRECTIONS AND CONCLUSIONS 231<br />

edge of language includes some knowledge of the relative frequencies of alternate forms for<br />

the same meaning <strong>and</strong> alternate meanings for the same form. This need not be seen as<br />

an additional \burden" on the language learner, a separate \coe cient" to be stored along<br />

with all the other syntactico-semantic knowledge. Rather, it should be a natural conse-<br />

quence of a spreading-activation model of language learning <strong>and</strong> language processing. It<br />

is probably premature to try to describe in much detail the relation between connectionist<br />

mental models <strong>and</strong> the patterns of preferences displayed by speakers, but a realistic model<br />

of the speaker's knowledge of senses should also include knowledge of the statistical pro les<br />

of the senses.<br />

There have been a number of corpus-based studies on inducing the possible ar-<br />

gument structures for various verbs from large corpora (e.g. Manning 1993), but most of<br />

them have not had adequate sources of semantic knowledge about the arguments. Al-<br />

though part-of-speech tagged corpora have been available for some time, we are just now<br />

beginning to have parsers that are robust enough to allow ustorecordthesyntax of the<br />

argumentsofaverb in adequately (i.e. beyond a bigram or trigram grammar based on<br />

part-of speech tagging). At the same time, resources such asWordNet (Miller et al. 1990;<br />

Fellbaum 1998) are enabling us to do at least limited semantic typing of the heads of the<br />

argument NPs. 2<br />

We should therefore be in a good position to undertake a corpus study of the<br />

argument structure of see, using the frame descriptions as a starting point <strong>and</strong> inducing<br />

statistical pro les of the syntax <strong>and</strong> semantics of the arguments of each sense. A similar<br />

study is being undertaken by Dan Jurafsky <strong>and</strong> his associates for several thous<strong>and</strong> words,<br />

many of them polysemous, in connection with the <strong>Frame</strong>Net project (Lowe et al. 1997;<br />

Baker et al. 1998).<br />

For the reasons just mentioned, we would expect that a careful study of corpus<br />

examples of see will show that even though there is a considerable overlap in the syntax <strong>and</strong><br />

semantics of the arguments of di erent senses, the relative frequencies of di erent argument<br />

patterns will be quite di erent for di erent senses (as shown in similar studies of other<br />

2 For the present, however, natural language processing systems must use primarily syntactic frames <strong>and</strong><br />

relatively \shallow" semantics, because \real" semantics not only involves more world knowledge than any<br />

current NLP system incorporates, but also requires too much processing time. This is not necessarily a bad<br />

thing; the time constraints on human language processing suggest that people also do a very broad, \shallow"<br />

sort of processing, (cf. Jurafsky 1992), rather than performing a \deep" logical sort of deduction such as<br />

that envisioned by Hobbs et al. (1993). People do, however, integrate more types of evidence, especially<br />

semantic evidence, more rapidly than current AI systems.

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