Attention, intentions, and the structure of discourse
Computational Linguistics
Tense quantifiers, and contexts
Computational Linguistics - Special issue on tense and aspect
A computational model of the semantics of tense and aspect
Computational Linguistics - Special issue on tense and aspect
The mapping unit approach to subcategorization
HLT '91 Proceedings of the workshop on Speech and Natural Language
Syntactic and semantic knowledge in the DELPHI unification grammar
HLT '90 Proceedings of the workshop on Speech and Natural Language
Computational Models of Discourse
Computational Models of Discourse
The CIRCUS System as Used in MUC-3
The CIRCUS System as Used in MUC-3
Integrating top-down and bottom-up strategies in a text processing system
ANLC '88 Proceedings of the second conference on Applied natural language processing
A centering approach to pronouns
ACL '87 Proceedings of the 25th annual meeting on Association for Computational Linguistics
Providing a unified account of definite noun phrases in discourse
ACL '83 Proceedings of the 21st annual meeting on Association for Computational Linguistics
Discourse relations and defeasible knowledge
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
A computational mechanism for pronominal reference
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
Causal and temporal text analysis: the role of the domain model
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Information extraction as a basis for high-precision text classification
ACM Transactions on Information Systems (TOIS)
Recovering nonlinearly distributed knowledge: Computing discourse structure in factual reports
Natural Language Engineering
A prosodic analysis of discourse segments in direction-giving monologues
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
BBN: description of the PLUM system as used for MUC-5
MUC5 '93 Proceedings of the 5th conference on Message understanding
BBN: description of the PLUM system as used for MUC-4
MUC4 '92 Proceedings of the 4th conference on Message understanding
BEN: description of the PLUM system as used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
Survey of the Message Understanding Conferences
HLT '93 Proceedings of the workshop on Human Language Technology
Progress in information extraction
TIPSTER '96 Proceedings of a workshop on held at Vienna, Virginia: May 6-8, 1996
BBN's PLUM Probabilistic Language Understanding system
TIPSTER '93 Proceedings of a workshop on held at Fredericksburg, Virginia: September 19-23, 1993
Using decision trees for conference resolution
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Using temporal cues for segmenting texts into events
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
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Discourse comprises those phenomena that usually do not arise when processing a single sentence. It appears to be the most difficult and probably the least understood aspect of automated message understanding. Five out of fifteen sites on a MUC-3 survey listed discourse as their main weakness and an area in which to concentrate future research. Virtually all systems presented here take a sentence-by-sentence approach to text understanding. Parsing and domain-dependent interpretation of sentences or sentence fragments (usually the latter) are followed by modules that attempt to connect these interpretations into a coherent whole. This paper gives an overview of the modules that make the transition from the interpretation of sentences to the interpretation of the text that contains these sentences. Systems presented in this paper exhibit various degrees of the following discourse understanding capabilities:• identifying portions of text that describe different domain events; this includes the capability of recognizing a single event and the capability of distinguishing multiple events;• resolving references:- pronoun references, e.g., finding the referent of It in the sentence It took place this morning,- proper name references, e.g., understanding that Luis Galan may be referred to as Senator Galan;- definite references, e.g., deciding what is the referent for The attack in the sentence The attack look us by surprise.• discourse representation : representation at the message level.