ACE Time Normalization (TERN) 2004 English Training Data v 1.0
|Item Name:||ACE Time Normalization (TERN) 2004 English Training Data v 1.0|
|Author(s):||Lisa Ferro, Laurie Gerber, Janet Hitzeman, Elizabeth Lima, Beth Sundheim|
|LDC Catalog No.:||LDC2005T07|
|Release Date:||February 15, 2005|
|Project(s):||ACE, GALE, TIDES|
|Application(s):||automatic content extraction, information extraction, question-answering, summarization, temporal analysis|
LDC User Agreement for Non-Members
|Online Documentation:||LDC2005T07 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Ferro, Lisa, et al. ACE Time Normalization (TERN) 2004 English Training Data v 1.0 LDC2005T07. Web Download. Philadelphia: Linguistic Data Consortium, 2005.|
ACE Time Normalization (TERN) 2004 English Training Data v 1.0 was developed by the Linguistic Data Consortium (LDC) and the National Institute of Standards and Technology (NIST) with support from the Automatic Content Extraction (ACE) program. It contains 862 files totalling 306,000 words of English news and treebank text.
This release contains the English training data prepared for the 2004 Time Expression Recognition and Normalization (TERN) Evaluation, sponsored by the ACE program. The evaluation was held in August 2004 and a workshop in September 2004. Evaluation participants received this data for training purposes, and it is now being released for general use.
The annotation specifications for this corpus were developed under DARPA's Translingual Information Detection Extraction and Summarization (TIDES) program, with continuing support from ACE.
The purpose of this corpus and the TERN evaluation is to advance the state of the art in the automatic recognition and normalization of natural language temporal expressions. In most language contexts such expressions are indexical. For example, with "Monday," "last week," or "three months starting October 1," one must know the narrative reference time in order to pinpoint the time interval being conveyed by the expression. In addition, for data exchange purposes, it is essential that the identified interval be rendered according to an established standard, i.e., normalized. Accurate identification and normalization of temporal expressions is in turn essential for the temporal reasoning being demanded by advanced NLP applications such as question answering, information extraction, and summarization.
The data in this corpus is divided into three data sets, ace_2002, ace_2003, and ace_2004. Here are the genres and sources included in this corpus:
- bnews - Broadcast news data from TDT4 Multilingual Text and Annotations (LDC2005T16)
- nwire - Newswire data from TDT4 Multilingual Text and Annotations (LDC2005T16)
- npaper - Washington Post articles (ace_2002 only)
- arabic_treebank - Data from the Arabic Treebank 1 Corpus English translations from the MT-2003 translation data set
- chinese_treebank - Data from the Chinese Treebank Version 4 English translations from the Chinese Treebank English Parallel Text Corpus
And here are the details for the data sets:
The data in this corpus includes the original source files in SGML format (.sgm) and the annotated files, also in SGML format (.tmx.sgml).
None at this time.
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