A challenging problem in open information extraction and text mining is the learning of the selectional restrictions of semantic relations. We propose a minimally supervised bootstrapping algorithm that uses a single seed and a recursive lexico-syntactic pattern to learn the arguments and the supertypes of a diverse set of semantic relations from the Web. We evaluate the performance of our algo...

Automatically judging sentences for their grammaticality is potentially useful for several purposes — evaluating language technology systems, assessing language competence of second or foreign language learners, and so on. Previous work has examined parser ‘byproducts’, in particular parse probabilities, to distinguish grammatical sentences from ungrammatical ones. The aim of the present paper ...

Subjective reports of confidence are frequently used as a measure of awareness in a variety of fields, including artificial grammar learning. However, little is known about what information is used to make confidence judgments and whether there are any possible sources of information used to discriminate between items that are unrelated to confidence. The data reported here replicate an earlier...

In the present study, using event-related functional magnetic resonance imaging, we investigated a group of participants on a grammaticality classification task after they had been exposed to well-formed consonant strings generated from an artificial regular grammar. We used an implicit acquisition paradigm in which the participants were exposed to positive examples. The objective of this study...

Large number of researchers consider essay as a tool to judge learning outcomes and intellectual capabilities and to assess the organized and integrated thoughts. Due to increase in the number of universities students and distance and ubiquitous e-learning approaches, the intention of using Computer-based Assessment Systems has rise rapidly in a decade. Manual grading of students' essays requir...

We describe a formal framework for interpretation of words and compounds in a discourse context which integrates a symbolic lexicon/grammar, word-sense probabilities, and a pragmatic component. The approach is motivated by the need to handle productive word use. In this paper, we concentrate on compound nominals. We discuss the inadequacies of approaches which consider compound interpretation a...

We propose a method of acquiring attribute words for a wide range of objects from Japanese Web documents. The method is a simple unsupervised method that utilizes the statistics of words, lexico-syntactic patterns, and HTML tags. To evaluate the attribute words, we also establish criteria and a procedure based on question-answerability about the candidate word.

In this article we will outline two different vocabularies, both extensions of the lemon model, for representing diachronic lexicosemantic data on the Semantic Web. This is especially useful for representing the evolution of scientific terminologies where many terms are polysemous and or imported from other languages. The first vocabulary, polyLemon, allows for the representation of data about ...

Lexico-semantic networks such as WordNet have been criticized about the nature of the senses they distinguish as well as on the way they define these senses. In this article, we present a possible solution to overcome these limits by defining the sense of words from the way they are used. More precisely, we propose to differentiate the senses of a word from a network of lexical cooccurrences bu...