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» Instance-Based Natural Language Generation
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ACL
1993
15 years 3 months ago
Towards History-Based Grammars: Using Richer Models for Probabilistic Parsing
We describe a generative probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorporates...
Ezra Black, Frederick Jelinek, John D. Lafferty, D...
101
Voted
ER
2010
Springer
90views Database» more  ER 2010»
15 years 1 months ago
W-Ray: A Strategy to Publish Deep Web Geographic Data
Abstract. This paper introduces an approach to address the problem of accessing conventional and geographic data from the Deep Web. The approach relies on describing the relevant d...
Helena Piccinini, Melissa Lemos, Marco A. Casanova...
JOLLI
2010
106views more  JOLLI 2010»
15 years 28 days ago
Second-Order Abstract Categorial Grammars as Hyperedge Replacement Grammars
rder Abstract Categorial Grammars as Hyperedge Replacement Grammars Makoto Kanazawa National Institute of Informatics 2–1–2 Hitotsubashi, Chiyoda-ku, Tokyo, 101–8430, Japan A...
Makoto Kanazawa
164
Voted
TLDI
2003
ACM
135views Formal Methods» more  TLDI 2003»
15 years 7 months ago
Typed compilation of recursive datatypes
Standard ML employs an opaque (or generative) semantics of datatypes, in which every datatype declaration produces a new type that is different from any other type, including othe...
Joseph Vanderwaart, Derek Dreyer, Leaf Petersen, K...
FLAIRS
2008
15 years 4 months ago
Learning a Probabilistic Model of Event Sequences from Internet Weblog Stories
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...
Mehdi Manshadi, Reid Swanson, Andrew S. Gordon