OLAC Record
oai:www.ldc.upenn.edu:LDC2020L02

Metadata
Title:Chinese Lexical Resources for Gender, Number, Animacy
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Chen, Song, et al. Chinese Lexical Resources for Gender, Number, Animacy LDC2020L02. Web Download. Philadelphia: Linguistic Data Consortium, 2020
Contributor:Chen, Song
Yuan, Jiahong
Ma, Xiaoyi
Strassel, Stephanie
Date (W3CDTF):2020
Date Issued (W3CDTF):2020-09-15
Description:*Introduction* Chinese Lexical Resources for Gender, Number, Animacy was developed by the Linguistic Data Consortium (LDC) and consists of gender, number, and animacy lexicons produced in support of the DARPA DEFT program. Gender, number and animacy are lexical indicators useful for named entity tagging, including the detection of person mentions in 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 data sources. *Data* This corpus was created by extracting information from newswire texts in Chinese Gigaword Fifth Edition (LDC2011T13) in the following steps: (1) segmenting source documents into sentences; (2) converting any traditional Chinese script to simplified Chinese; (3) tagging all sentences for parts-of-speech; (4) developing queries to detect patterns; and (5) building lexicons based on frequency counts and entity types. The resulting resources include dictionaries of Chinese animate nominals and names; Chinese nominals and name with gender and number predicted; and other dictionaries of Chinese nominals, names, verbs and pronouns. Each dictionary contains frequency information as well as the features in question. All lexical data is presented as UTF-8 encoded plain text. *Samples* Please view this gender sample and name 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: 95591 KB
Identifier:LDC2020L02
https://catalog.ldc.upenn.edu/LDC2020L02
ISBN: 1-58563-944-3
ISLRN: 535-036-387-989-4
DOI: 10.35111/jmrz-8y15
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/LDC2020L02
Rights Holder:Portions © 2000-2010 Agence France Presse, © 1991-2010 Central News Agency (Taiwan), © 2006-2010 China Military Online, © 2006-2010 Chinanews.com, © 2006-2010 Guangming Daily, © 2006-2010 Peoples Daily, © 1998, 2000-2003 SPH AsiaOne, Ltd., © 1990-2010 Xinhua News Agency, © 2003, 2005, 2007, 2009, 2011, 2020 Trustees of the University of Pennsylvania
Type (DCMI):Text
Type (OLAC):lexicon

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:LDC2020L02
DateStamp:  2021-01-01
GetRecord:  OAI-PMH request for simple DC format

Search Info

Citation: Chen, Song; Yuan, Jiahong; Ma, Xiaoyi; Strassel, Stephanie. 2020. Linguistic Data Consortium.
Terms: area_Asia country_CN dcmi_Text iso639_cmn olac_lexicon


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Up-to-date as of: Thu Oct 24 7:31:11 EDT 2024