Recognizing Expressions of Commonsense Psychology in English Text (bibtex)
by Gordon, Andrew S., Kazemzadeh, Abe, Nair, Anish and Petrova, Milena
Abstract:
Many applications of natural language processing technologies involve analyzing texts that concern the psychological states and processes of people, including their beliefs, goals, predictions, explanations, and plans. In this paper, we describe our efforts to create a robust, large-scale lexical-semantic resource for the recognition and classification of expressions of commonsense psychology in English Text. We achieve high levels of precision and recall by hand-authoring sets of local grammars for commonsense psychology concepts, and show that this approach can achieve classification performance greater than that obtained by using machine learning techniques. We demonstrate the utility of this resource for large-scale corpus analysis by identifying references to adversarial and competitive goal in political speeches throughout U.S. history.
Reference:
Recognizing Expressions of Commonsense Psychology in English Text (Gordon, Andrew S., Kazemzadeh, Abe, Nair, Anish and Petrova, Milena), In Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL), 2003.
Bibtex Entry:
@inproceedings{gordon_recognizing_2003,
	address = {Sapporo, Japan},
	title = {Recognizing {Expressions} of {Commonsense} {Psychology} in {English} {Text}},
	url = {http://ict.usc.edu/pubs/Recognizing%20Expressions%20of%20Commonsense%20Psychology%20in%20English%20Text.PDF},
	abstract = {Many applications of natural language processing technologies involve analyzing texts that concern the psychological states and processes of people, including their beliefs, goals, predictions, explanations, and plans. In this paper, we describe our efforts to create a robust, large-scale lexical-semantic resource for the recognition and classification of expressions of commonsense psychology in English Text. We achieve high levels of precision and recall by hand-authoring sets of local grammars for commonsense psychology concepts, and show that this approach can achieve classification performance greater than that obtained by using machine learning techniques. We demonstrate the utility of this resource for large-scale corpus analysis by identifying references to adversarial and competitive goal in political speeches throughout U.S. history.},
	booktitle = {Proceedings of the 41st {Annual} {Meeting} of the {Association} for {Computational} {Linguistics} ({ACL})},
	author = {Gordon, Andrew S. and Kazemzadeh, Abe and Nair, Anish and Petrova, Milena},
	month = jul,
	year = {2003},
	keywords = {The Narrative Group}
}
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