Proper names present problems for the automatic understanding of unrestricted text. One problem for processing text is that proper names occur very frequently in news text, and important names are likely to be mentioned many times. In addition, a proper name can occur in variant forms in an article. Yet the classification of unknown names in text is crucial for NLP systems to understand a text, especially news text. Although much of the work being done in identification and categorization is based on the internal structure of names and local contexts, little work has been reported on the discourse properties of names.
Key words are words that provide clues to identify preceding or following proper names.
For example, titles, degrees, and affiliations are important sources for recognizing personal names. Proper names related to organizations have various key words such as Corp ., Inc ., Association . These can be definite criteria indicating company or organization. A key word is not always enough to categorize a proper name. For instance, a company name can be designated by a contracted name form without a key word.