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1
Learning to Understand Natural Language with Less Human Effort
In: DTIC (2015)
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2
Enabling Efficient Intelligence Analysis in Degraded Environments
In: DTIC (2013)
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3
Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
In: DTIC (2013)
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4
Pictures from Words, Pictures from Text: Constructing Pictorial Representations of Meaning from Text
In: DTIC (2009)
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5
Semantic Web Services with Web Ontology Language (OWL-S) - Specification of Agent-Services for DARPA Agent Markup Language (DAML)
In: DTIC (2006)
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6
Analysis of Free-Form Battlefield Reports with Shallow Parsing Techniques
In: DTIC AND NTIS (2004)
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7
Shifting the Computational Paradigm
In: DTIC AND NTIS (2004)
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8
A Syntactic Approach to Foundational Proof-Carrying Code
In: DTIC AND NTIS (2002)
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9
A Survey of Current Paradigms in Machine Translation
In: DTIC (1998)
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10
Schema and Data Conflict Resolution Across Distributed Graphical ASN.1 Databases.
In: DTIC AND NTIS (1994)
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11
A Simplified Account of Polymorphic References. Revised
In: DTIC AND NTIS (1993)
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12
Naive Physics, Event Perception, Lexical Semantics, and Language Acquisition
In: DTIC AND NTIS (1993)
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13
Tipster Shogun System (Joint GE-CMU): MUC-4 Test Results and Analysis
In: DTIC (1992)
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14
Pipes: Linguistic Support for Ordered Asynchronous Invocations
In: DTIC AND NTIS (1992)
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15
Very High Speed Integrated Circuits (VHSIC) Hardware Description Language (VHDL) Syntax and Semantics Summary
In: DTIC AND NTIS (1991)
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16
The Pegasys Environment for Graphical Documentation of Large Programs
In: DTIC AND NTIS (1991)
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17
Incremental Interpretation
In: DTIC (1990)
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18
A Cockpit Natural Language Study: Vocabulary and Grammar Analyses.
In: DTIC AND NTIS (1988)
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19
A Report Generator Volume 2
In: DTIC AND NTIS (1988)
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20
What's so Hard about Understanding Language
In: DTIC AND NTIS (1988)
Abstract: This paper reports empirical work in artificial intelligence (AI) on natural language processing. The kind of AI that we are interested in is cognitive modeling. The goal is to describe some aspect of human mental activity, say problem solving or language use, in computational terms. The central issues is this kind of study turn out to be representation and reasoning (corresponding roughly to data structures and control in computer programs. In this paper we examine several problems in language understanding involving semantic ambiguity, anaphoric reference, and metonymy.
Keyword: *ARTIFICIAL INTELLIGENCE; *COMPREHENSION; *COMPUTER PROGRAMS; *NATURAL LANGUAGE; AMBIGUITY; ARTIFICIAL INTELLIGENCE; COGNITION; COMPUTATIONS; Cybernetics; DATA BASES; HUMANS; INFORMATION PROCESSING; LANGUAGE; Linguistics; MENTAL ABILITY; MODELS; NATURAL LANGUAGE; PE61153N; PROBLEM SOLVING; REASONING; SEMANTICS; WU442C022
URL: http://www.dtic.mil/docs/citations/ADA232847
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA232847
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