Modeling the Emergence of an Exemplar Verb in Construction Learning

Modeling the Emergence of an Exemplar Verb in Construction Learning Libby Barak , Afsaneh Fazly , and Suzanne Stevenson Department of Computer Science University of Toronto {libbyb,afsaneh,suzanne}@cs.toronto. edu Abstract Using a computational model of verb argument structure learn- ing, we study a key assumption of the usage-based theory: that the acquisition of a construction relies heavily on the existence of a high-frequency exemplar verb that accounts for a large proportion of usages of that construction in the input. Im- portantly, unlike the psycholinguistic experiments that focus on the learning of an artificial novel construction using novel verbs, here we examine the acquisition of the English sen- tential complement construction from naturalistic input. Our results provide new insights into exemplar-based learning in the context of naturalistic input with multiple semantic classes, and a diverse set of constructions for the verbs. Introduction Verb argument structure acquisition is a challenging task that children face early in their life. In order to correctly use a verb, children must learn the syntactic structures that the verb appears in, as well as the semantic relations among the ar- guments of the verb. Nonetheless, children learn the correct usages of many verbs at a young age. Usage-based theories of language acquisition suggest that children learn the argu- ment structure regularities mainly from the input they receive. These theories are supported by observing that children ini- tially learn verb argument structures on an item-by-item ba- sis, and only later generalize their verb-specific knowledge into abstract constructions that map a particular syntactic form to certain semantic properties (Tomasello, 2000). The distributional properties of verb usages in child- directed input highly affect the developmental path of the ac- quisition of argument structure constructions. For example, several studies have shown that children tend to learn high- frequency verbs earlier (Naigles & Hoff-Ginsberg, 1998; Matthews, Lieven, Theakston, & Tomasello, 2005), and that they are more likely to detect grammatical anomalies in sen- tences containing such verbs (Theakston, 2004; Ambridge et al., 2008). Moreover, the relative frequency of a verb with a particular syntactic construction has been shown to posi- tively correlate with the ability of young children to recall sentences containing that verb (Kidd, Lieven, & Tomasello, 2006, 2010). Most importantly, there is evidence that the ac- quisition of a construction is connected to a high-frequency exemplar verb; e.g., give is the exemplar for the ditransitive construction (Goldberg, 1999; Kidd et al., 2006, 2010). In fact, several studies have shown that it is not just the amount of overall exposure to a construction that affects its acquisi- tion, but instead learning seems to be facilitated by a high number of usages of a particular exemplar verb (Casenhiser & Goldberg, 2005; Wonnacott et al., 2008). The above psycholinguistic studies perform experiments on children, and hence are often limited in the number of items they can investigate, and in how much they can tease apart the various interacting factors that might play a role on the results. For example, the sentence recall tasks performed by Kidd et al. (2010) examine only eight complement-taking verbs (CTVs). Moreover, due to their choice of verbs, they cannot separate the effects of overall frequency and relative construction frequency on their results. Using a computa- tional model of argument structure learning, we extend these investigations into a larger set of CTVs, and also manipu- late input in such a way that we can tease apart the effects of the various frequency factors. Our results are consistent with the findings of Kidd et al. (2006, 2010), that the rela- tive frequency of a verb with a sentential complement is pos- itively correlated with the ability of young children to recall sentences containing the verb in that construction. However, through computational modeling, we are further able to pro- vide evidence on the interaction of verb frequency and rela- tive construction frequency in accounting for their findings. Studies examining the effect of a high-frequency exemplar verb in the acquisition of novel constructions often do so in the context of an artificial language learning task, where chil- dren are introduced to a novel verb mapped to a novel (or fa- miliar) event semantics (Casenhiser & Goldberg, 2005; Won- nacott et al., 2008). We use our computational model to in- vestigate the existence and role of an exemplar verb in the acquisition of the English finite sentential complement (SC) syntax — a complex structure that has received less atten- tion in the experimental studies (though see Kidd et al., 2006, 2010). Importantly, the use of a model enables us to vary dis- tributional properties of the input in a way not easily achieved in a human experimental setting. Inspired by the work of Casenhiser and Goldberg (2005), we study the role of a high- frequency exemplar verb (think) for the acquisition of SC, but we do so in the context of a diverse set of verbs and con- structions, as is the case in the naturalistic input that children receive. Our results suggest that the acquisition of a construc- tion is facilitated by the relative frequency with which a class of semantically-related verbs appear with the syntactic form associated with the construction. The Computational Model We use an extended version of the verb argument structure ac- quisition model of Alishahi and Stevenson (2008), which we have used in studying the acquisition of mental state verbs (Barak, Fazly, & Stevenson, 2012). This model has appropri- ate characteristics for our study: (i) it focuses on argument structure learning, and the interplay between syntax and se- mantics; (ii) it is probabilistic and hence can naturally reflect