James Pustejovsky

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In this paper, I will discuss four major topics relating to current research in lexical semantics: methodology, descriptive coverage, adequacy of the representation, and the computational usefulness of representations. In addressing these issues, I will discuss what I think are some of the central problems facing the lexical semantics community, and suggest(More)
In this paper we provide a description of TimeML, a rich specification language for event and temporal expressions in natural language text, developed in the context of the AQUAINT program on Question Answering Systems. Unlike most previous work on event annotation, TimeML captures three distinct phenomena in temporal markup: (1) it systematically anchors(More)
Tempeval-2 comprises evaluation tasks for time expressions, events and temporal relations, the latter of which was split up in four sub tasks, motivated by the notion that smaller subtasks would make both data preparation and temporal relation extraction easier. Manually annotated data were provided for six languages: Chinese, English, French, Italian,(More)
The TempEval task proposes a simple way to evaluate automatic extraction of temporal relations. It avoids the pitfalls of evaluating a graph of inter-related labels by defining three sub tasks that allow pairwise evaluation of temporal relations. The task not only allows straightforward evaluation, it also avoids the complexities of full temporal parsing.
Within the SemEval-2013 evaluation exercise, the TempEval-3 shared task aims to advance research on temporal information processing. It follows on from TempEval-1 and -2, with: a three-part structure covering temporal expression, event, and temporal relation extraction; a larger dataset; and new single measures to rank systems – in each task and in general.(More)
This paper investigates a machine learning approach for temporally ordering and anchoring events in natural language texts. To address data sparseness, we used temporal reasoning as an oversampling method to dramatically expand the amount of training data, resulting in predictive accuracy on link labeling as high as 93% using a Maximum Entropy classifier on(More)
The MIT Encyclopedia of the Cognitive Sciences (MITECS) brings together 471 brief articles on a very wide range of topics within cognitive science. The general editors worked with advisory editors in six contributing fields, including Gennaro Chierchia on Linguistics and Language and Michael I. Jordan and Stuart Russell on Computational Intelligence. MITECS(More)
We present Evita, an application for recognizing events in natural language texts. Although developed as part of a suite of tools aimed at providing question answering systems with information about both temporal and intensional relations among events, it can be used independently as an event extraction tool. It is unique in that it is not limited to any(More)
In this paper we examine the role of events within a theory of lexical semantics. We propose a configurational theory of event structure and examine how it contributes to a lexical semantic theory for natural language. In particular, we argue that an event structure can provide a distinct and useful level of representation for linguistic analysis involving(More)