OLAC Record
oai:www.ldc.upenn.edu:LDC2019T03

Metadata
Title:DEFT Chinese Committed Belief Annotation
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Tracey, Jennifer, et al. DEFT Chinese Committed Belief Annotation LDC2019T03. Web Download. Philadelphia: Linguistic Data Consortium, 2019
Contributor:Tracey, Jennifer
Arrigo, Michael
Kuster, Neil
Strassel, Stephanie
Date (W3CDTF):2019
Date Issued (W3CDTF):2019-02-15
Description:*Introduction* DEFT Chinese Committed Belief Annotation was developed by the Linguistic Data Consortium (LDC) and consists of approximately 83,000 tokens of Chinese discussion forum text annotated for "committed belief," which marks the level of commitment displayed by the author to the truth of the propositions expressed in the text. DARPA's Deep Exploration and Filtering of Text (DEFT) program aimed to address remaining capability gaps in state-of-the-art natural language processing technologies related to inference, causal relationships and anomaly detection. LDC supported the DEFT program by collecting, creating and annotating a variety of language resources. LDC has also released DEFT Spanish Committed Belief Annotation (LDC2019T09). *Data* The source data is Chinese discussion forum web text collected by LDC. Annotations fall into one of four categories: committed belief, non-committed belief, reported belief and not applicable. Further information about the annotation methodology is contained in the documentation accompanying this release. This publication contains 140 files (83,016 tokens). Annotation files are stored in XML format, and source documents are stored in plain text format. Both types of files are encoded in UTF-8. *Samples* Please view this source sample and annotation sample. *Updates* None at this time. *Acknowledgement* This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government.
Extent:Corpus size: 6616 KB
Identifier:LDC2019T03
https://catalog.ldc.upenn.edu/LDC2019T03
ISBN: 1-58563-873-0
ISLRN: 233-896-127-699-9
Language:Mandarin Chinese
Language (ISO639):cmn
License:LDC User Agreement for Non-Members: https://catalog.ldc.upenn.edu/license/ldc-non-members-agreement.pdf
Medium:Distribution: Web Download
Publisher:Linguistic Data Consortium
Publisher (URI):https://www.ldc.upenn.edu
Relation (URI):https://catalog.ldc.upenn.edu/docs/LDC2019T03
Rights Holder:Portions © 2019 Trustees of the University of Pennsylvania
Type (DCMI):Text
Type (OLAC):primary_text

OLAC Info

Archive:  The LDC Corpus Catalog
Description:  http://www.language-archives.org/archive/www.ldc.upenn.edu
GetRecord:  OAI-PMH request for OLAC format
GetRecord:  Pre-generated XML file

OAI Info

OaiIdentifier:  oai:www.ldc.upenn.edu:LDC2019T03
DateStamp:  2020-01-06
GetRecord:  OAI-PMH request for simple DC format

Search Info

Citation: Tracey, Jennifer; Arrigo, Michael; Kuster, Neil; Strassel, Stephanie. 2019. Linguistic Data Consortium.
Terms: area_Asia country_CN dcmi_Text iso639_cmn olac_primary_text


http://www.language-archives.org/item.php/oai:www.ldc.upenn.edu:LDC2019T03
Up-to-date as of: Mon Sep 7 10:38:28 EDT 2020