Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Rebecca J. Schiffman

dblp:99/92 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 1986
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Information extraction and text analysis · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis › coreference resolution
reference resolution
0.011986
Recovering Implicit Information · ACL 1986

Methods — techniques the papers use, named apart from their topics

syntactic-semantic-pragmatic processing · 0.0prolog · 0.0
YearPublicationVenuePosition
1986 Recovering Implicit Information
abstract
This paper describes the SDC PUNDIT, (Prolog UNDerstands Integrated Text), system for processing natural language messages.1 PUNDIT, written in Prolog, is a highly modular system consisting of distinct syntactic, semantic and pragmatics components.Each component draws on one or more sets of data, including a lexicon, a broad-coverage grammar of EngLish, semantic verb decompositions, rules mapping between syntactic and semantic constituents, and a domain model.This paper discusses the communication between the syntactic, semantic and pragmatic modules that is necessary for making implicit linguistic information explicit.The key is letting syntax and semantics recognize missing linguistic entities as implicit entities, so that they can be labelled as such, and referenee resolution can be directed to find specific referents for the entities.In this way the task of making implicit linguistic information explicit becomes a subset of the tasks performed by reference resolution.The success of this approach is dependent on marking missing syntactic constituents as elided and missing semantic roles as ESSENTIAL so that reference resolution can know when to look for referents.
Martha Palmer, Deborah A. Dahl, Rebecca J. Schiffman, Lynette Hirschman, Marcia C. Linebarger, John Dowding
ACL3