ACE 2004 Multilingual Training Corpus

Item Name: ACE 2004 Multilingual Training Corpus
Author(s): Alexis Mitchell, Stephanie Strassel, Shudong Huang, Ramez Zakhary
LDC Catalog No.: LDC2005T09
ISBN: 1-58563-334-8.
ISLRN: 789-870-824-708-5
DOI: https://doi.org/10.35111/8m4r-v312
Release Date: March 15, 2005
Member Year(s): 2005
DCMI Type(s): Text
Data Source(s): broadcast news, newswire, telephone conversations
Project(s): ACE, GALE, TIDES
Application(s): automatic content extraction
Language(s): English, Standard Arabic, Mandarin Chinese
Language ID(s): eng, arb, cmn
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2005T09 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Mitchell, Alexis, et al. ACE 2004 Multilingual Training Corpus LDC2005T09. Web Download. Philadelphia: Linguistic Data Consortium, 2005.
Related Works: View

Introduction

ACE 2004 Multilingual Training Corpus was developed by the Linguistic Data Consortium (LDC) and contains the various genre text in English (158,000 words), Chinese (307,000 characters, 154,000 words), and Arabic (151,000 words) annotated for entities and relations.

This corpus represents the complete set of English, Arabic, and Chinese training data for the 2004 Automatic Content Extraction (ACE) technology evaluation created by LDC with support from the ACE Program and additional assistance from the DARPA TIDES (Translingual Information Detection, Extraction and Summarization) Program. This data was previously distributed as an e-corpus (LDC2004E17) to participants in the 2004 ACE evaluation.

The objective of the ACE program is to develop automatic content extraction technology to support automatic processing of human language in text form. In September 2004, sites were evaluated on system performance in six areas: Entity Detection and Recognition (EDR), Entity Mention Detection (EMD), EDR Co-reference, Relation Detection and Recognition (RDR), Relation Mention Detection (RMD), and RDR given reference entities. All tasks were evaluated in three languages: English, Chinese and Arabic.

The current publication consists of the official training data for these evaluation tasks. A seventh evaluation area, Timex Detection and Recognition, is supported by ACE Time Normalization (TERN) 2004 English Training Data v 1.0 (LDC2005T07). The TERN corpus source data largely overlaps with the English source data contained in the current release.

For more information about linguistic resources for the ACE program, including annotation guidelines, task definitions, free annotation tools and other documentation, please visit LDC's ACE website.

Data

Here is a breakdown of the data amounts by language:

  English Chinese Arabic
Genre Files Words Files Words Characters Files Words
Broadcast News 220 60,291 314 67,702 135,405 304 63,238
Newswire 128 59,840 226 60,251 120,502 253 63,122
Chines Treebank 37 12,337 106 25,749 51,499    
Arabic Treebank 58 12,855       132 25,010
Fisher CTS 8 12,630          
Totals 451 157,953 646 153,703 307,406 689 151,360

All files are annotated for entities and relations. Annotators tag all mentions of each entity within a document, whether named, nominal or pronominal. For every mention, the annotator identifies the maximal extent of the string that represents the entity, and labels the head of each mention. Annotators also identify relations between entities and their temporal attributes. Relations that are supported by explicit textual evidence are distinguished from those that depend on contextual inference on the part of the reader.

The files are stored in four separate formats:

  • APF (.apf.xml) - The Official ACE Program Format.
  • ALF (.alf.xml) - The Ace LDC Format is an intermediate format similar to APF designed to store all annotation content represented in the AG files.
  • AG (-pp.ag.xml) - The LDC Annotation Graph Format (postprocessed). LDC's internal annotation files format for ACE. These files can be viewed with LDC's free ACE annotation tools.
  • Source (.sgm) - Source text files in with SGML tagging.

Samples

The files listed below are samples from the English data. They should provide a good example of the material in this corpus.

The World is a co-production of Public Radio International and the British Broadcasting Corporation and is produced at WGBH Boston.

Updates

None at this time.

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