While reading times are often used to measure working memory load, frequency effects (such as surprisal or n-gram frequencies) also have strong confounding effects on reading times. This work uses a naturalistic audio corpus with magnetoencephalographic (MEG) annotations to measure working memory load during sentence processing. Alpha oscillations in posterior regions of the brain have been fou...

Children use syntax to guide verb learning in a process known as syntactic bootstrapping. Recent work explores how syntactic bootstrapping works-how it begins, and how it interacts with progress in syntax acquisition. We review evidence for three claims about the mechanisms and representations underlying syntactic bootstrapping: (1) Learners are biased to represent linguistic knowledge in a use...

1. Introduction Possessive relations are fundamental in linguistic descriptions. The alienability between a possessum and its possessor, in particular, has received much attention in the literature (see Antrim, 1996 and a recent collection by Coene & D'hulst, 2003, for reviews). The issue of alienability concerns whether a nominal entity holds an intrinsic relation with its possessor. Such a re...

This paper describes the Emory system for recognizing textual entailment as used for the RTE4 track at the TAC 2008 competition. We use a supervised machine learning approach to train a classifier over a variety of lexical, syntactic, and semantic metrics. We treat the output of each metric as a feature, and train a classifier on the provided data from the previous RTE tracks. As a result, our ...

Syntactically ambiguous sentences are sometimes read faster than disambiguated strings. Models of parsing have explained this tendency by appealing either to a race in the construction of alternative structures or to reanalysis. However, it is also possible that readers of ambiguous sentences save time by strategically underspecifying interpretations of ambiguous attachments. In a self-paced re...

We show that it is possible to learn the contexts for linguistic operations which map a semantic representation to a surface syntactic tree in sentence realization with high accuracy. We cast the problem of learning the contexts for the linguistic operations as classification tasks, and apply straightforward machine learning techniques, such as decision tree learning. The training data consist ...

An important aspect of language acquisition involves learning the syntactic nonadjacent dependencies that hold between words in sentences, such as subject/verb agreement or tense marking in English. Despite successes in statistical learning of adjacent dependencies, the evidence is not conclusive for learning nonadjacent items. We provide evidence that discovering nonadjacent dependencies is po...

Contributors: Michael Lewis Schneir (author), Wendy Kingdom (section editor), Any Whereat editor)

Reports in the sentence processing literature on whether untrained speakers reliably disambiguate syntactic phrase structure ambiguities with prosody have shown mixed results. Allbritton et al (1996), Straub (1997), and Snedeker et al (1999) found little to no evidence of prosodic disambiguation of syntax when other factors resolved the ambiguity, and argued that prosodic disambiguation is prod...