Purpose
– The purpose of this paper is to present a system for recognition of location names in ancient books written in languages, such as Chinese, in which proper names are not signaled by an initial capital letter.
Design/methodology/approach
– Rule-based and statistical methods were combined to develop a set of rules for identification of product-related location names in the local chronicles of Guangdong. A name recognition system, with functions of document management, information extraction and storage, rule management, location name recognition, and inquiry and statistics, was developed using Microsoft's .NET framework, SQL Server 2005, ADO.NET and XML. The system was evaluated with precision ratio, recall ratio and the comprehensive index, F.
Findings
– The system was quite successful at recognizing product-related location names (F was 71.8 percent), demonstrating the potential for application of automatic named entity recognition techniques in digital collation of ancient books such as local chronicles.
Research limitations/implications
– Results suffered from limitations in initial digitization of the text. Statistical methods, such as the hidden Markov model, should be combined with an extended set of recognition rules to improve recognition scores and system efficiency.
Practical implications
– Electronic access to local chronicles by location name saves time for chorographers and provides researchers with new opportunities.
Social implications
– Named entity recognition brings previously isolated ancient documents together in a knowledge base of scholarly and cultural value.
Originality/value
– Automatic name recognition can be implemented in information extraction from ancient books in languages other than English. The system described here can also be adapted to modern texts and other named entities.
Named Entity Recognition in Equipment Support Field using Tri-Training Algorithm and Text Information Extraction Technology
