Progress in natural language processing requires increasing amounts of data and annotation in a growing variety of languages, and research in named entity extraction is no exception. While the value of richlyannotated, large-scale multilingual corpora is undeniable, costs for producing such data are high, underscoring the value of shared resources. As part of the US Governmentsponsored Automatic Content Extraction Program (ACE), the University of Pennsylvania's Linguistic Data Consortium has recently created a number of shared resources to support technology evaluations in multilingual information extraction. This paper discusses the challenges of multilingual corpus development, with a particular focus on Chinese named entities. It concludes with a description of the corpora developed to support this research.
The objective of the ACE program is to develop technology to automatically infer from human language data the entities being mentioned, the relations among these entities that are directly expressed, and the events in which these entities participate. Data sources include audio and image data in addition to pure text, and Arabic and Chinese in addition to English. The effort involves defining the research tasks in detail, collecting and annotating data needed for training, development, and evaluation, and supporting the research with evaluation tools and research workshops. This program began with a pilot study in 1999. The next evaluation is scheduled for September 2004.
Progress in human language technology requires increasing amounts of data and annotation in a growing variety of languages. Research in Named Entity extraction is no exception. Linguistic Data Consortium is creating annotated corpora to support information extraction in English, Chinese, Arabic, and other languages for a variety of US Government-sponsored programs. This paper covers the scope of annotation and research tasks within these programs, describes some of the challenges of multilingual corpus development for entity extraction, and concludes with a description of the corpora developed to support this research.
