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
ISBN: 1-58563-331-3
ISLRN: 357-991-519-054-6
Release Date: February 15, 2005
Member Year(s): 2005
DCMI Type(s): Text
Data Source(s): newswire
Project(s): ACE, GALE, TIDES
Application(s): automatic content extraction, information extraction, question-answering, summarization, temporal analysis
Language(s): English
Language ID(s): eng
License(s): 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.
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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:

And here are the details for the data sets:

Data Set Genre Words Documents
ace_2002 bnews 17,922 85
npaper 14,682 17
nwire 34,134 78
Total 66,738 180
ace_2003 bnews 34,681 147
nwire 58,592 102
Total 93,273 249
ace_2004 bnews 61,621 222
nwire 58,543 116
arabic_treebank 13,466 58
chinese_treebank 12,522 37
Total 146,452 433
Grand Totals 306,463 862

The data in this corpus includes the original source files in SGML format (.sgm) and the annotated files, also in SGML format (.tmx.sgml).


For example of the data in this corpus, please view this source sample (SGML) and annotation sample (SGML).


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