Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data
MARIUS A. PAŞCA · 2008
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.