Summary of the paper
| Title | Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data |
|---|---|
| Authors | Marius Pasca |
| 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. |
| Language | Single language |
| Topics | Information Extraction, Information Retrieval, Named Entity recognition, Text mining |
Full paper |
Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data |
Slides |
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| Bibtex | @InProceedings{PASCA08.886, author = {Marius Pasca}, title = {Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data}, booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)}, year = {2008}, month = {may}, date = {28-30}, address = {Marrakech, Morocco}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-4-0}, note = {http://www.lrec-conf.org/proceedings/lrec2008/}, language = {english} } |