R. Grishman

Publications
Influence

Message Understanding Conference- 6: A Brief History

R. Grishman, B. Sundheim
Computer Science
COLING
5 August 1996

We have recently completed the sixth in a series of "Message Understanding Conferences" which are designed to promote and evaluate research in information extraction. Expand

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The NomBank Project: An Interim Report

Adam Meyers, R. Reeves, +4 authors R. Grishman
Computer Science
FCP@NAACL-HLT
2004

This paper describes NomBank, a project that will provide argument structure for instances of common nouns in the Penn Treebank II corpus. Expand

Overview of the TAC 2010 Knowledge Base Population Track

Heng Ji, Heng Ji, R. Grishman, H. T. Dang, Kira Griffitt, J. Ellis
Computer Science
2010

In this paper we give an overview of the Knowledge Base Population (KBP) track at TAC 2010. Expand

Joint Event Extraction via Recurrent Neural Networks

T. Nguyen, Kyunghyun Cho, R. Grishman
Computer Science
HLT-NAACL
1 June 2016

We propose to do event extraction in a joint framework with bidirectional recurrent neural networks, thereby benefiting from the advantages of the two models as well as addressing issues inherent in the existing approaches. Expand

Discovering Relations among Named Entities from Large Corpora

T. Hasegawa, S. Sekine, R. Grishman
Computer Science
ACL
21 July 2004

We propose an unsupervised method for relation discovery from large corpora. Expand

Relation Extraction: Perspective from Convolutional Neural Networks

T. Nguyen, R. Grishman
Computer Science
VS@HLT-NAACL
1 June 2015

We introduce a convolutional neural network for relation extraction that automatically learns features from sentences and minimizes the dependence on external toolkits and resources. Expand

A Procedure for Quantitatively Comparing the Syntactic Coverage of English Grammars

E. Black, Steven P. Abney, +12 authors T. Strzalkowski
Computer Science, Philosophy
HLT
19 February 1991

The problem of quantitatively comparing the performance of different broad-coverage grammars of English has to date resisted solution. Expand

Comlex Syntax: Building a Computational Lexicon

R. Grishman, C. Macleod, Adam Meyers
Computer Science
COLING
5 August 1994

We describe the design of Comlex Syntax, a computational lexicon providing detailed syntactic information for approximately 38,000 English headwords. Expand

A maximum entropy approach to named entity recognition

R. Grishman, Andrew Borthwick
Computer Science
1999

This thesis describes a novel statistical named-entity (i.e. “proper name”) recognition system known as “MENE” (Maximum Entropy Named Entity). Expand

NOMLEX: a lexicon of nominalizations

C. Macleod, R. Grishman, Adam Meyers, Leslie Barrett, R. Reeves
Computer Science
1998

NOMLEX is a dictionary of English nominalizations being developed by the Proteus Project at New York University. Expand

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