Appendix E: MUC-7 Named Entity Task Definition (version 3.5)

Appendix F: MUC-7 Coreference Task Definition (version 3.0)

Combining n-gram based statistics with traditional methods for named entity recognition

In this paper, we show three main results. First, we show that an n-gram dataset built from a large web crawl, as opposed to data from the specific target domain, can be used to perform the task of named entity recognition with reasonable accuracy. Second, we show that for complex domains, such as the MUC-7 NER task, the Lex method may not perform as well as other methods, due largely in part t...

Appendix D: MUC-7 Information Extraction Task Definition (version 5.1)

Information extraction in the sense of the Message Understanding Conferences has been traditionally defined as the extraction of information from a text in the form of text strings and processed text strings which are placed into slots labeled to indicate the kind of information that can fill them. So, for example, a slot labeled NAME would contain a name string taken directly out of the text o...

CRL/NMSU: description of the CRL/NMSU systems used for MUC-6

CRL submitted two systems for the Named Entity task . One of these (Basic) is an improved version of the CRL name recognizer developed in phase one of Tipster[1]. The second (AutoLearn) is a system which learns automatically from training data . The Basic system had approximatel y six man months of work in its original development . Improvements for MUC-6 were carried out by one graduate studen...

NameTag(TM) Japanese and Spanish Systems as Used for MET

We have participated in the Multilingual Entity Task (MET) for Japanese and Spanish using SRA's multilingual text-indexing software called NameTag TM. Its English version was used for the Named Entity Task (NE) in MUC-6 [2]. The NameTag Japanese and Spanish systems were customized to accommodate the MET-specific requirements and were able to achieve high performance in both recall and precision.