OLAC Record
oai:www.ldc.upenn.edu:LDC2012T10

Metadata
Title:Catalan TimeBank 1.0
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Sauri, Roser, and Toni Badia. Catalan TimeBank 1.0 LDC2012T10. Web Download. Philadelphia: Linguistic Data Consortium, 2012
Contributor:Sauri, Roser
Badia, Toni
Date (W3CDTF):2012
Date Issued (W3CDTF):2012-07-18
Description:Catalan TimeBank 1.0 was developed by researchers at Barcelona Media and consists of Catalan texts in the AnCora corpus annotated with temporal and event information according to the TimeML specification language. TimeML (Pusteyovsky, et al., 2005) is a schema for annotationg eventualities and time expressions in natural language as well as the temporal relations among them, thus facilitating the task of extraction, representation and exchange of temporal information. Catalan Timebank 1.0 is annotated in three levels, marking events, time expressions and event metadata. The TimeML annotation scheme was tailored for the specifics of the Catalan language. Temporal relations in Catalan present distinctions of verbal mood (e.g., indicative, subjunctive, conditional, etc.) and grammatical aspect (e.g., imperfective) which are absent in English. Catalan TimeBank 1.0 joins the family of TimeBank annotated corpora which includes languages such as English, Spanish, Italian, French, Korean and Chinese. Through their common layer of annotation, these corpora provide resoures useful for multilingual temporal extraction and processing, such as multilingual text entailment, opinion mining or question answering. LDC has released the following corpora incorporating TimeBank annotation: TimeBank 1.2 LDC2006T08, FactBank 1.0 LDC2009T23 and ModeS TimeBank 1.0 LDC2012T01. *Data* Catalan TimeBank 1.0 contains stand-off annotations for 210 documents with over 75,800 tokens (including punctuation marks) and 68,000 tokens (excluding punctuation). The source documents are from the EFE news agency, the ACN Catalan news agency2 and the Catalan version of the El Períodico newspaper, and span the period from January to December 2000. The AnCora corpus is the largest multilayer annotated corpus of Spanish and Catalan. AnCora contains 400,000 words in Spanish and 275,000 words in Catalan. The AnCora documents are annotated on many linguistic levels including stucture, syntax, dependencies, semantics and pragmatics.That information is not included in this release, but it can be mapped to the present annotations. The data contained in the AnCora corpus has been used in several international natural language processing evaluations such as CoNLL-2006, CoNLL-2007 and SemEval-2007. The corpus is freely available from the Centre de Llenguatge i Computació (CLiC). *Samples* (Click to view full sized image.) *Updates* Additional information, updates, bug fixes may be available in the LDC catalog entry for this corpus at LDC2012T10.
Extent:Corpus size: 4608 KB
Identifier:LDC2012T10
https://catalog.ldc.upenn.edu/LDC2012T10
ISBN: 1-58563-618-5
ISLRN: 442-580-062-511-9
Language:Catalan
Language (ISO639):cat
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/LDC2012T10
Rights Holder: Portions © 2012 Roser Saurí, Toni Badia, © 2012 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
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OAI Info

OaiIdentifier:  oai:www.ldc.upenn.edu:LDC2012T10
DateStamp:  2019-01-03
GetRecord:  OAI-PMH request for simple DC format

Search Info

Citation: Sauri, Roser; Badia, Toni. 2012. Linguistic Data Consortium.
Terms: area_Europe country_ES dcmi_Text iso639_cat olac_primary_text


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Up-to-date as of: Sun Sep 1 18:18:39 EDT 2019