Abstract Meaning Representation (AMR) Annotation Release 2.0

Version 1.0

Knight, Kevin; Badarau, Bianca; Baranescu, Laura; Bonial, Claire; Bardocz, Madalina; Griffitt, Kira; Hermjakob, Ulf; Marcu, Daniel; Palmer, Martha; O'Gorman, Tim; Schneider, Nathan, 2017, "Abstract Meaning Representation (AMR) Annotation Release 2.0", https://hdl.handle.net/11272.1/AB2/8MN4GE, Abacus Data Network, V1

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Description	Abstract Meaning Representation (AMR) Annotation Release 2.0 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 39,260 English natural language sentences from broadcast conversations, 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 of a sentence largely independent of its syntax. LDC also released Abstract Meaning Representation (AMR) Annotation Release 1.0 (LDC2014T12). Data The source data includes discussion forums collected for the DARPA BOLT and DEFT programs, transcripts and English translations of Mandarin Chinese broadcast news programming from China Central TV, Wall Street Journal text, translated Xinhua news texts, various newswire data from NIST OpenMT evaluations and weblog data used in the DARPA GALE program. The following table summarizes the number of training, dev, and test AMRs for each dataset in the release. Totals are also provided by partition and dataset: Dataset Training Dev Test Totals BOLT DF MT 1061 133 133 1327 Broadcast conversation 214 0 0 214 Weblog and WSJ 0 100 100 200 BOLT DF English 6455 210 229 6894 DEFT DF English 19558 0 0 19558 Guidelines AMRs 819 0 0 819 2009 Open MT 204 0 0 204 Proxy reports 6603 826 823 8252 Weblog 866 0 0 866 Xinhua MT 741 99 86 Totals 36521 1368 1371 39260 For those interested in utilizing a standard/community partition for AMR research (for instance in development of semantic parsers), data in the “split” directory contains 39,260 AMRs split roughly 93%/3.5%/3.5% into training/dev/test partitions, with most smaller datasets assigned to one of the splits as a whole. Note that splits observe document boundaries. The “unsplit” directory contains the same 39,260 AMRs with no train/dev/test partition.
Subject	Other
Keyword	Linguistics

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Citation Metadata

Dataset Persistent ID	hdl:11272.1/AB2/8MN4GE
Publication Date	2017-06-15
Citation Date
Title	Abstract Meaning Representation (AMR) Annotation Release 2.0
Other ID	Linguistic Data Consortium: LDC2017T10 ISBN: 1-58563-802-1 ISLRN: 335-339-972-504-9
Author	Knight, Kevin Badarau, Bianca Baranescu, Laura Bonial, Claire Bardocz, Madalina Griffitt, Kira Hermjakob, Ulf Marcu, Daniel Palmer, Martha O'Gorman, Tim Schneider, Nathan
Contact	Use email button above to contact. Abacus support
Description	Abstract Meaning Representation (AMR) Annotation Release 2.0 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 39,260 English natural language sentences from broadcast conversations, 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 of a sentence largely independent of its syntax. LDC also released Abstract Meaning Representation (AMR) Annotation Release 1.0 (LDC2014T12). Data The source data includes discussion forums collected for the DARPA BOLT and DEFT programs, transcripts and English translations of Mandarin Chinese broadcast news programming from China Central TV, Wall Street Journal text, translated Xinhua news texts, various newswire data from NIST OpenMT evaluations and weblog data used in the DARPA GALE program. The following table summarizes the number of training, dev, and test AMRs for each dataset in the release. Totals are also provided by partition and dataset: Dataset Training Dev Test Totals BOLT DF MT 1061 133 133 1327 Broadcast conversation 214 0 0 214 Weblog and WSJ 0 100 100 200 BOLT DF English 6455 210 229 6894 DEFT DF English 19558 0 0 19558 Guidelines AMRs 819 0 0 819 2009 Open MT 204 0 0 204 Proxy reports 6603 826 823 8252 Weblog 866 0 0 866 Xinhua MT 741 99 86 Totals 36521 1368 1371 39260 For those interested in utilizing a standard/community partition for AMR research (for instance in development of semantic parsers), data in the “split” directory contains 39,260 AMRs split roughly 93%/3.5%/3.5% into training/dev/test partitions, with most smaller datasets assigned to one of the splits as a whole. Note that splits observe document boundaries. The “unsplit” directory contains the same 39,260 AMRs with no train/dev/test partition.
Subject	Other
Keyword	Linguistics (ACV)
Producer	Linguistic Data Consortium (University of Pennsylvania) (LDC) https://www.ldc.upenn.edu/ SDL/Language Weaver, Inc http://www.sdl.com/ Computational Language and Educational Research Group (University of Colorado) http://clear.colorado.edu/start/index.html Information Sciences Institute (University of Southern California) http://www.isi.edu/home
Production Date	2017-06-15
Production Place	Philadelphia
Grant Information	National Science Foundation: Grant NSF: 0910992 Defense Advanced Research Projects Agency: HR0011-11-C-0150 Defense Advanced Research Projects Agency: BOLT - HR0011-11-C-0145 Defense Advanced Research Projects Agency: DEFT - FA-8750-13-2-0045
Distributor	Linguistic Data Consortium (University of Pennsylvania) (LDC) https://www.ldc.upenn.edu/
Deposit Date	2017-11-02
Time Period Covered	Start: 1997 ; End: 2017
Date of Collection	Start: 1997 ; End: 2017
Kind of Data	Linguistic data
Series	LDC: Linguistic Data Consortium
Data Sources	Discussion forum, broadcast conversation, weblogs, web collection, newswire

Geospatial Metadata

Geographic Coverage	China France Israel Taiwan, Province of China United States

Social Science and Humanities Metadata

Study Level Error Notes	DCMI type: TextApplication: Coreference resolution, entity extraction, information extraction, semantic role labellingLanguage: EnglishLanguage ID: enProject: BOLT, DEFT, GALE, ACE Previous handle https://hdl.handle.net/11272/P5FEC has been deprecated

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