The Role of the Syntax/Semantics in SLA: Computational Experiments in Verb Classification. Tsang, V. & Stevenson, S. In The 15th Annual CUNY Conference on Human Sentence Processing, New York, March, 2002.
abstract   bibtex   

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, and 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 and S. Stevenson, 2001. Automatic verb classification based on statistical distribution of argument structure. Computational Linguistics, 27(3): 393–408.

S. Pinker (1989). Learnability and Cognition. MIT Press.

@InProceedings{	  tsang3,
  author	= {Vivian Tsang and Suzanne Stevenson},
  title		= {The Role of the Syntax/Semantics in SLA: Computational
		  Experiments in Verb Classification},
  booktitle	= {The 15th Annual CUNY Conference on Human Sentence
		  Processing},
  address	= {New York},
  month		= {March},
  year		= {2002},
  abstract	= {<p> 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.
		  
		  <p> 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.
		  
		  <p> 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.</p> <p> Earlier work
		  has shown that such statistical syntactic features within
		  English can be used to classify English verbs into semantic
		  classes (Merlo &amp; 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.
		  
		  <p> 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.
		  
		  <P><B>References</B>
		  
		  <P> J. Gillette, L. Gleitman, H. Gleitman, and A. Lederer
		  (1999). Human simulation of vocabulary learning.
		  <I>Cognition</i>, 73(2): 135--176.
		  
		  <P> L. Gleitman (1990). Structural sources of verb meaning.
		  <i>Language Acquisition</i>, 1(1): 3--55.
		  
		  <P> R. Helms-Park (2001). Evidence of lexical transfer in
		  learner syntax. <I>Studies in Second Language
		  Acquisition</I>, 23(1): 71--102. <P> S. Inagaki (1997).
		  Japanese and Chinese learners' acquisition of the
		  narrow-range rules for the dative alternation in English.
		  <i>Language Learning</I>, 47(4): 637--669.
		  
		  <P> B. Levin, (1993). <I>English Verb Classes and
		  Alternations</I>. University of Chicago Press.
		  
		  <P> P. Merlo and S. Stevenson, 2001. Automatic verb
		  classification based on statistical distribution of
		  argument structure. <I>Computational Linguistics</I>,
		  27(3): 393--408.
		  
		  <P> S. Pinker (1989). <I>Learnability and Cognition</I>.
		  MIT Press.}
}
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