Learning Argument Structure Generalizations

Conclusion

This work suggests an account of both how and why children form the argument structure generalizations they do. The paper’s main theoretical contribution is to explicitly relate generally recognized facts about language acquistion to generally recognized facts about categorization. Many researchers in language acquisition allude to general categorization processes, but very little in the way of specifics have been offered. We argue that children initially generalize at the level of specific verbs plus argument slots (Tomasello’s “verb islands”) because the verb in an argument frame is an excellent predictor of overall sentence meaning. We argue further that children eventually generalize away from specific verbs to form more abstract argument structure constructions because the argument frame or construction has roughly equivalent cue validity as a predictor of overall sentence meaning than the morphological form of the verb, and has much greater category validity. That is, initially children attend to the complex of cues: that of verb and construction; eventually, attention focuses on the construction because the construction has equivalent cue validity and much greater category validity as compared with individual verbs, given the task of sentence comprehension. The construction is at least as reliable and much more available.

We further argue that the input is structured in such a way as to make the generalization from verb islands to argument structure constructions straightforward. The paper’s main empirical contribution is the finding that one particular verb accounts for the lion’s share of instances of each argument frame considered in an extensive corpus study on the Bates et al. (1988) corpus, in both mothers’ and 28 month old children’s speech. The dominance of a single verb in the construction facilitates the association of the meaning of the verb in the construction with the construction itself, allowing learners to get a “fix” on the construction’s meaning. In this way, grammatical constructions may arise developmentally as generalizations over lexical items in particular patterns.

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* The authors are grateful for helpful discussions with Cindy Fisher, Gregory Murphy, Dedre Gentner. We thank Aarre Laakso and Dan Jackson for writing programs to help us analyze the corpus data, and Giulia Bencini, Bill Croft, Dan Jackson, Aarre Laakso, Gregory Murphy and two anonymous reviewers for helpful comments. This research was funded in part by the first author’s NSF Grant SBR-9873450.

1 It is quite possible that “dumb” attentional processing, as opposed to strategic inferences, may be all that is required insofar as hearing a word serves to direct the learner’s attention to the referent of that word (seeSmith, Jones, & Landau, 1996, for discussion of this idea)

2 This type of learning is reminiscent of Carey and Bartlett’s (1978) “fast-mapping.” Carey and Bartlett demonstrated that children were able to infer the meaning of an unknown word (chromium) when used as an adjective in a context that contrasted it explicitly with known color terms. Specifically, a teacher asked 3 year old children individually to “show me the chromium tray, not the red one, the chromium one.” Because there were only two trays, one red, one olive, children were able to infer that chromium must be a word for the color olive. However, the present suggestion for verb-learning can apply earlier and more generally since it does not presuppose any comprehension of the syntactic structures of the language, nor a contrastive context, but simply the knowledge of a small number of nouns and/or pronouns.

3 Findings of this sort demonstrate that detailed verb-specific knowledge about frequencies of usage clearly influence adult grammar. Knowledge of specific verbs continues to be useful in several ways. Verbs are required for more specific interpretation, for example the contrast between give and hand, pass, throw, or send. Verb-centered categories are also required for occasional idiosyncratic patterns (e.g., help vs aid). Moreover, as many have observed, individual verbs play a key role in determining exceptions to constructional generalizations (see below).

4 The study involved descriptions of people belonging to one of two clubs, with members’ descriptions varying on five 4-valued dimensions.

5 Interestingly enough, Elio and Anderson (1984) also found that when subjects were explicitly asked to form hypotheses about what criteria governed category membership, the advantage of learning the centered instances first disappeared. They therefore conclude that the advantage is only evident when the learning is implicit. Implicit learning involves knowledge that is not accessible to consciousness, fairly complex and abstract, an incidental consequence of some task demand, and preserved in case of amnesia (Seger, 1994). Relevantly, language learning is an excellent example of implicit learning, since it is largely learned below the level of consciousness, is very complex and ultimately quite abstract, is a consequence of trying to communicate, and is preserved in cases of amnesia.

6 Stimuli in this experiment also consisted of non-linguistic stimuli: variable sized semi-circles with variably oriented radial lines.

7 Zipf long ago noted that highly frequent words account for most linguistic tokens (Zipf, 1935). Although he did not claim that there should be a single most highly frequent word that would correspond to the meaning of the overall pattern, nor did Zipf’s work prepare us for the fact that a single verb accounts for such a lion’s share of the tokens, his observation suggests that we may find a similar pattern in constructions other than argument structure constructions.

8 Gropen et al. separated uses which they considered idiomatic. Inclusion of these uses would increase the overall frequency of give. The numbers here do not include them.

9 Tell, in our small sample of 54 appeared an equal number of times as give. We believe the high number of instances of tell is an artifact of the book-reading context, since only one instance occured in a non-story context. The other 10 occurrences are all directly related to the task of reading the story; in fact the second object in 8 out of 10 instances is story.

10 See Cartwright and Brent (1997) and Morris and Cottrell (1999) for suggestions of how more intricate syntactic category and grammatical relation properties may be acquired on the basis of distributional properties of the input.

11 Ninio also includes data from a single English speaking child: Travis (fromTomasello, 1992); however the English data presented is highly equivocal, since one of Travis’ first two SVO expressions (Big Bird ride horsie), involved “ride,” a word unattested in any of the Hebrew speaking children’s early transcripts. Travis’ second VO combination was Find-it funny which does not involve an object, since it is parsed by Ninio as a non-referential verbal clitic. Also, only one out of four of the earliest VO and SVO utterances involved the idea “obtaining” although this idea is said to account for 78.1% of the earliest Hebrew utterances. None of these discrepancies are material to the current proposal, since we do not claim that light verbs are necessarily the very first verbs uttered.

12 Silverstein (1976) observed that patients that are stereotypical in terms of being inanimate and causally affected are often unmarked, pace Ninio.

13 Kruschke discusses how this tendency is so strong that it can account for the neglect of base rate information (the inverse base rate effect discovered by Medin and Edelson (1988)). In Medin and Edelson’s study, subjects were taught to classify diseases on the basis of symptoms. Subjects were trained to discriminate disease C (for common) and R (for rare), with C being presented three times as often as R. In the training, every instance of C had two symptoms, I and PC, and every instance of R had two symptoms, I and PR. Since I appeared with both diseases, it was an imperfect predictor; PC was a perfect predictor of the common disease, PR was a perfect predictor of the rare disease.When tested with the ambiguous symptom I, subjects acted in accord with the disease’s overall frequency and chose the common disease, C. But when presented with conflicting symptoms PC and PR, people tended to choose the rare disease, contrary to what would be expected if base rates were taken into account in a simple way. Krushke (1996) suggests that subjects learn that the shared symptom I tends to be misleading for the less frequent disease