In this paper, we present a workbench for semi-automatic ontology
population from textual documents. It provides an environment for
mapping the linguistic extractions with the domain ontology thanks
to knowledge acquisition rules. Those rules are activated when a
pertinent linguistic tag is reached. Those linguistic tags are then
mapped to a concept, one of its attributes or even a semantic relation
between several concepts. The rules instantiate these concepts, attributes
and relations in the knowledge base constrained by the domain ontology.
This paper deals with the underlying knowledge capture process and
presents the first experiments realized on a real client application
from the legal publishing domain.
%0 Conference Paper
%1 Amardeilh2005
%A Amardeilh, Florence
%A Laublet, Philippe
%A Minel, Jean-Luc
%B K-CAP '05: Proceedings of the 3rd international conference on Knowledge
capture
%C New York, NY, USA
%D 2005
%I ACM
%K annotation nlp population
%P 161--168
%R http://doi.acm.org/10.1145/1088622.1088651
%T Document annotation and ontology population from linguistic extractions
%U http://portal.acm.org/citation.cfm?id=1088622.1088651&coll=GUIDE&dl=GUIDE&CFID=27226889&CFTOKEN=65948633
%X In this paper, we present a workbench for semi-automatic ontology
population from textual documents. It provides an environment for
mapping the linguistic extractions with the domain ontology thanks
to knowledge acquisition rules. Those rules are activated when a
pertinent linguistic tag is reached. Those linguistic tags are then
mapped to a concept, one of its attributes or even a semantic relation
between several concepts. The rules instantiate these concepts, attributes
and relations in the knowledge base constrained by the domain ontology.
This paper deals with the underlying knowledge capture process and
presents the first experiments realized on a real client application
from the legal publishing domain.
%@ 1-59593-163-5
@inproceedings{Amardeilh2005,
abstract = {In this paper, we present a workbench for semi-automatic ontology
population from textual documents. It provides an environment for
mapping the linguistic extractions with the domain ontology thanks
to knowledge acquisition rules. Those rules are activated when a
pertinent linguistic tag is reached. Those linguistic tags are then
mapped to a concept, one of its attributes or even a semantic relation
between several concepts. The rules instantiate these concepts, attributes
and relations in the knowledge base constrained by the domain ontology.
This paper deals with the underlying knowledge capture process and
presents the first experiments realized on a real client application
from the legal publishing domain.},
added-at = {2009-06-12T18:16:40.000+0200},
address = {New York, NY, USA},
author = {Amardeilh, Florence and Laublet, Philippe and Minel, Jean-Luc},
biburl = {https://www.bibsonomy.org/bibtex/262640b36c7e6cd934843ba08100d2269/jmora},
booktitle = {K-CAP '05: Proceedings of the 3rd international conference on Knowledge
capture},
doi = {http://doi.acm.org/10.1145/1088622.1088651},
interhash = {24a928cd92d58a435e3b4826ffc71947},
intrahash = {62640b36c7e6cd934843ba08100d2269},
isbn = {1-59593-163-5},
keywords = {annotation nlp population},
location = {Banff, Alberta, Canada},
owner = {jmora},
pages = {161--168},
publisher = {ACM},
timestamp = {2009-06-12T18:31:21.000+0200},
title = {Document annotation and ontology population from linguistic extractions},
url = {http://portal.acm.org/citation.cfm?id=1088622.1088651&coll=GUIDE&dl=GUIDE&CFID=27226889&CFTOKEN=65948633},
year = 2005
}