@inproceedings{pasca-2008-low,
title = "Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data",
author = "Pa{\c{s}}ca, Marius",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2008/pdf/886_paper.pdf",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data
%A Paşca, Marius
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 may
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F pasca-2008-low
%X 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.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/886_paper.pdf
Markdown (Informal)
[Low-Complexity Heuristics for Deriving Fine-Grained Classes of Named Entities from Web Textual Data](http://www.lrec-conf.org/proceedings/lrec2008/pdf/886_paper.pdf) (Paşca, LREC 2008)
ACL