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Abstract:
Theories of verb classification have elaborated a
detailed mapping from underlying semantics to overt syntactic
behavior (Pinker, 1989; Levin, 1993). This syntax/semantics
mapping appears to aid language Acquisition, as the child uses
syntactic cues to induce properties of verb semantics (Gleitman,
1990; Gillette et al., 1999). Recent experiments in Second
Language Acquisition (SLA) reveal another fascinating role played
by this mapping: second language (L2) learners assume that L2
verbs allow the same syntactic constructions as semantically
similar verbs in the native language (L1) (Helms-Park, 2001;
Inagaki, 1997). Thus, L2 learners appear to generalize
their knowledge of the syntax/semantics mapping in L1 to learn
the syntax of verbs in L2 --- an instance of "transfer effects"
in SLA.
We have investigated these transfer effects in a
set of computational experiments that explore the ability of L1
features to aid in the learning of L2 verb classes. Verb
classes encapsulate the syntax/semantics mapping, and have thus
been assumed to underlie the above SLA observations. We
model the observed behavior in our experiments as the
computational process of determining the appropriate class for an
L2 verb, on the basis of semantic and syntactic similarities
between verbs in L1 and L2.
Specifically, we select 16 verbs from each of two
semantic classes in English --- the L2 for our study. We
then select a set of verbs in Chinese --- the L1 for our study
--- that are translations of the L2 verbs in a bilingual (English
and Chinese) corpus. We determine syntactic features of the
verbs related to the semantic class distinctions, and collect
statistics over both the English verbs and their Chinese
translations, from the bilingual corpus. We then use these
features to train a system to classify the English verbs.
Earlier work has shown that such statistical
syntactic features within English can be used to classify English
verbs into semantic classes (Merlo & Stevenson 2001).
Here we find that, analogously to the SLA observations, the
syntactic behavior of L1 verbs (as captured in the Chinese
statistical features) transfers over to L2 (English) verbs,
aiding in their classification. In classifying the English
verbs (a task with chance performance of 50%), we achieve an
accuracy of 80% using a combination of English and Chinese
features, significantly outperforming monolingual features on the
same task.
We conclude that the syntax/semantics mapping for
verbs, which plays a role in first language acquisition, may also
be exploited crosslinguistically in SLA. Our computational
experiments support the hypothesis that L2 learners use the
mapping between the semantics and syntax of verbs in their L1, in
acquiring properties of verbs in L2. Furthermore, our
experiments elaborate a possible mechanism underlying this
transfer of knowledge --- namely, the statistical analysis of
verb behavior and its relation to semantic classes.
References
J. Gillette, L. Gleitman, H. Gleitman, & A.
Lederer (1999). Human simulation of vocabulary
learning. Cognition, 73(2): 135-176.
L. Gleitman (1990). Structural sources of
verb meaning. Language Acquisition, 1(1): 3-55.
R. Helms-Park (2001). Evidence of lexical
transfer in learner syntax. Studies in Second Language
Acquisition, 23(1): 71-102.
S. Inagaki (1997). Japanese and Chinese
learners' acquisition of the narrow-range rules for the dative
alternation in English". Language Learning, 47(4):
637-669.
B. Levin, (1993). English Verb Classes and
Alternations. University of Chicago Press.
P. Merlo, & S. Stevenson, 2001.
Automatic verb classification based on statistical distribution
of argument structure. Computational Linguistics, 27(3):
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S. Pinker (1989). Learnability and
Cognition. MIT Press.
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