His primary areas of study are Artificial intelligence, Natural language processing, TimeML, Linguistics and Temporal annotation. The Artificial intelligence study combines topics in areas such as Machine learning, Information retrieval and Data mining. He works in the field of Natural language processing, namely Natural language.
His study looks at the relationship between Linguistics and topics such as Certainty, which overlap with Epistemic modality. His biological study spans a wide range of topics, including Context and Markup language. His Lexical semantics study integrates concerns from other disciplines, such as Lexical item, Lexical choice and Lexicon.
His primary areas of investigation include Artificial intelligence, Natural language processing, Natural language, Linguistics and Annotation. His Artificial intelligence research integrates issues from Event and Information retrieval. His research investigates the connection between Natural language processing and topics such as Lexical semantics that intersect with problems in Lexical functional grammar.
The various areas that James Pustejovsky examines in his Natural language study include Question answering, Semantics and Predicate. His studies in Lexical choice, Polysemy, Context, Coercion and Grammar are all subfields of Linguistics research. His work on Lexical chain as part of general Lexical choice research is frequently linked to Lexical grammar, bridging the gap between disciplines.
His primary areas of investigation include Artificial intelligence, Natural language processing, Human–computer interaction, Gesture and Health records. His Artificial intelligence study incorporates themes from Structure, Machine learning and Representation. His work on VerbNet as part of his general Natural language processing study is frequently connected to Modal, thereby bridging the divide between different branches of science.
His study on Human–computer interaction also encompasses disciplines like
Embodied cognition that intertwine with fields like Virtual machine and Event,
Object which is related to area like Computational model, Semantics, Human intelligence and Qualitative reasoning,
Situated which intersects with area such as Robot, Affordance, Visual arts and Concept learning,
Space and related Link and Modalities,
Avatar, Spatial cognition, Adaptation, Gesture recognition and Blocks world most often made with reference to Deixis. His Gesture study also includes
Action and related Salient, Context and Interactive Learning,
Perception which intersects with area such as Gaze, Body language, Facial expression and Embodied agent. His work in Sketch addresses subjects such as Modality, which are connected to disciplines such as Linguistics.
His scientific interests lie mostly in Human–computer interaction, Artificial intelligence, Natural language processing, Gesture and Annotation. His Human–computer interaction study also includes fields such as
Many of his research projects under Natural language processing are closely connected to Causal relations with Causal relations, tying the diverse disciplines of science together. The Gesture study which covers Ambiguity that intersects with Action, Perception, Context, Blocks world and Gesture recognition. His study explores the link between Annotation and topics such as Sentiment analysis that cross with problems in Training set.
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The generative lexicon
The syntax of event structure.
TimeML: Robust Specification of Event and Temporal Expressions in Text
James Pustejovsky;José M. Castaño;Robert Ingria;Roser Saurí.
New Directions in Question Answering (2003)
SemEval-2010 Task 13: TempEval-2
Marc Verhagen;Roser Sauri;Tommaso Caselli;James Pustejovsky.
meeting of the association for computational linguistics (2010)
SemEval-2007 Task 15: TempEval Temporal Relation Identification
Marc Verhagen;Robert Gaizauskas;Frank Schilder;Mark Hepple.
meeting of the association for computational linguistics (2007)
SemEval-2013 Task 1: TempEval-3: Evaluating Time Expressions, Events, and Temporal Relations
Naushad UzZaman;Hector Llorens;Leon Derczynski;James Allen.
joint conference on lexical and computational semantics (2013)
Natural Language Annotation for Machine Learning
James Pustejovsky;Amber Stubbs.
Machine Learning of Temporal Relations
Inderjeet Mani;Marc Verhagen;Ben Wellner;Chong Min Lee.
meeting of the association for computational linguistics (2006)
Robust relational parsing over biomedical literature: extracting inhibit relations.
James Pustejovsky;José M. Castaño;Jason Zhang;Maciej Kotecki.
pacific symposium on biocomputing (2001)
The Generative Lexicon
Christiane Fellbaum;James Pustejovsky.
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