Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data

Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC 2008)

Abstract

We introduce a low-complexity method for acquiring fine-grained classes of named entities from the Web. The method exploits the large amounts of textual data available on the Web, while avoiding the use of any expensive text processing techniques or tools. The quality of the extracted classes is encouraging with respect to both the precision of the sets of named entities acquired within various classes, and the labels assigned to the sets of named entities.