OLAC Record oai:www.ldc.upenn.edu:LDC2020T19

Metadata
Title:		DEFT Chinese Light and Rich ERE Annotation
Access Rights:		Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:		Chen, Song, Stephanie Strassel, and Justin Mott. DEFT Chinese Light and Rich ERE Annotation LDC2020T19. Web Download. Philadelphia: Linguistic Data Consortium, 2020
Contributor:		Chen, Song
		Strassel, Stephanie
		Mott, Justin
Date (W3CDTF):		2020
Date Issued (W3CDTF):		2020-08-17
Description:		*Introduction* DEFT Chinese Light and Rich ERE Annotation was developed by the Linguistic Data Consortium (LDC) and consists of 157 Chinese discussion forum documents annotated for entities, relations and events (ERE). 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 data sources. Light ERE annotation labels entity mentions for the target set of entity, relation and event types between and among those entities, including coreference. Rich ERE annotation expands types and tagging in the entities, relations, and events annotation tasks and replaces strict event coreference with a more loosely defined event hopper annotation. Further information about the annotation methodology is contained in the documentation accompanying this release. *Data* The source data in this release is Chinese discussion forum web text collected by LDC. All files (157) were annotated following Light ERE annotation guidelines; a subset (149) were also labeled with Rich ERE annotation. Below is a data summary: ERE Files Characters Entities (mentions) Fillers Relations Event Hoppers Light 157 164,038 6,444 (16,997) N/A 2,401 817 (1,107) Rich 149 134,745 6,924 (16,471) 792 2,298 1,736 (2,360) Source documents are in plain text format, annotation is in XML format, and both are UTF-8 encoded. *Samples* Please view the following samples: * Source (TXT) * Light ERE (XML) * Rich ERE (XML) *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: 15322 KB
Identifier:		LDC2020T19
		https://catalog.ldc.upenn.edu/LDC2020T19
		ISBN: 1-58563-941-9
		ISLRN: 971-396-989-375-3
		DOI: 10.35111/GMN6-C105
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/LDC2020T19
Rights Holder:		Portions © 2020 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:LDC2020T19
DateStamp:		2021-01-01
GetRecord:		OAI-PMH request for simple DC format
Search Info
Citation:		Chen, Song; Strassel, Stephanie; Mott, Justin. 2020. Linguistic Data Consortium.
Terms:		area_Asia country_CN dcmi_Text iso639_cmn olac_primary_text