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Abstract Meaning Representation (AMR) Annotation Release 3.0
Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2020. : https://www.ldc.upenn.edu, 2020
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Abstract Meaning Representation (AMR) Annotation Release 3.0 ...
Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2020
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3
Abstract Meaning Representation (AMR) Annotation Release 2.0
Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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4
Abstract Meaning Representation (AMR) Annotation Release 2.0 ...
Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2017
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5
Abstract Meaning Representation (AMR) Annotation Release 1.0
Knight, Kevin; Baranescu, Laura; Bonial, Claire. - : Linguistic Data Consortium, 2014. : https://www.ldc.upenn.edu, 2014
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6
HyTER Networks of Selected OpenMT08/09 Sentences
Dreyer, Markus; Marcu, Daniel. - : Linguistic Data Consortium, 2014. : https://www.ldc.upenn.edu, 2014
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7
HyTER Networks of Selected OpenMT08/09 Sentences ...
Dreyer, Markus; Marcu, Daniel. - : Linguistic Data Consortium, 2014
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8
Abstract Meaning Representation (AMR) Annotation Release 1.0 ...
Abstract:

Introduction

Abstract Meaning Representation (AMR) Annotation Release 1.0 was developed by the Linguistic Data Consortium (LDC), SDL/Language Weaver, Inc., the University of Colorado's Computational Language and Educational Research group and the Information Sciences Institute at the University of Southern California. It contains a sembank (semantic treebank) of over 13,000 English natural language sentences from newswire, weblogs and web discussion forums. AMR captures “who is doing what to whom” in a sentence. Each sentence is paired with a graph that represents its whole-sentence meaning in a tree-structure. AMR utilizes PropBank frames, non-core semantic roles, within-sentence coreference, named entity annotation, modality, negation, questions, quantities, and so on to represent the semantic structure ...
URL: https://catalog.ldc.upenn.edu/LDC2014T12
https://dx.doi.org/10.35111/0ync-7404
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9
Induction of Word and Phrase Alignments for Automatic Document Summarization ...
Daumé, Hal; Marcu, Daniel. - : arXiv, 2009
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10
ISI Chinese-English Automatically Extracted Parallel Text
Dragos Stefan Munteanu; Marcu, Daniel. - : Linguistic Data Consortium, 2007. : https://www.ldc.upenn.edu, 2007
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11
ISI Arabic-English Automatically Extracted Parallel Text
Dragos Stefan Munteanu; Marcu, Daniel. - : Linguistic Data Consortium, 2007. : https://www.ldc.upenn.edu, 2007
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12
ISI Chinese-English Automatically Extracted Parallel Text ...
Dragos Stefan Munteanu; Marcu, Daniel. - : Linguistic Data Consortium, 2007
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13
ISI Arabic-English Automatically Extracted Parallel Text ...
Dragos Stefan Munteanu; Marcu, Daniel. - : Linguistic Data Consortium, 2007
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14
Scalable Inference and Training of Context-Rich Syntactic Translation Models
Graehl, Jonathan; Galley, Michel; DeNeefe, Steve. - : Proceedings of COLING/ACL, 2006
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15
Scalable Inference and Training of Context-Rich Syntactic Translation Models ...
Galley, Michel; Graehl, Jonathan; Knight, Kevin. - : Columbia University, 2006
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16
What's in a Translation Rule
In: DTIC (2004)
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17
Generic Sentence Fusion is an Ill-Defined Summarization Task
In: DTIC (2004)
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18
Syntax-based Alignment of Multiple Translations: Extracting Paraphrases and Generating New Sentences
In: DTIC (2003)
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19
Statistical Phrase-Based Translation
In: DTIC (2003)
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20
A Noisy-Channel Approach to Question Answering
In: DTIC (2003)
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