Article

Document annotation and ontology population from linguistic extractions

Authors:

Florence Amardeilh,

Philippe Laublet,

Jean-Luc MinelAuthors Info & Claims

K-CAP '05: Proceedings of the 3rd international conference on Knowledge capture

Pages 161 - 168

https://doi.org/10.1145/1088622.1088651

Published: 02 October 2005 Publication History

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.

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Cited By

Bensattalah AChalal RNader F(2023)An Adaptive Semantic Annotation Tool for Teachers Based on Context-Aware and Internet of ThingsInternational Journal of Software Engineering and Knowledge Engineering10.1142/S021819402350034133:09(1355-1385)Online publication date: 7-Aug-2023
https://doi.org/10.1142/S0218194023500341
Soavi MZeni NMylopoulos JMich L(2022)Semantic Annotation of Legal Contracts with ContrattoAInformatics10.3390/informatics90400729:4(72)Online publication date: 20-Sep-2022
https://doi.org/10.3390/informatics9040072
Soavi MZeni NMylopoulos JMich L(2022)From Legal Contracts to Formal Specifications: A Systematic Literature ReviewSN Computer Science10.1007/s42979-022-01228-43:5Online publication date: 21-Jun-2022
https://doi.org/10.1007/s42979-022-01228-4
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Index Terms

Document annotation and ontology population from linguistic extractions
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
    2. Natural language processing

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cover image ACM Conferences

K-CAP '05: Proceedings of the 3rd international conference on Knowledge capture

October 2005

234 pages

ISBN:1595931635

DOI:10.1145/1088622

General Chairs:
Peter Clark
The Boeing Company, USA
,
Guus Schreiber
Free University of Amsterdam, The Netherlands

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 02 October 2005

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K-Cap05: Third International Conference on Knowledge Capture 2005

October 2 - 5, 2005

Alberta, Banff, Canada

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Overall Acceptance Rate 55 of 198 submissions, 28%

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Cited By

Bensattalah AChalal RNader F(2023)An Adaptive Semantic Annotation Tool for Teachers Based on Context-Aware and Internet of ThingsInternational Journal of Software Engineering and Knowledge Engineering10.1142/S021819402350034133:09(1355-1385)Online publication date: 7-Aug-2023
https://doi.org/10.1142/S0218194023500341
Soavi MZeni NMylopoulos JMich L(2022)Semantic Annotation of Legal Contracts with ContrattoAInformatics10.3390/informatics90400729:4(72)Online publication date: 20-Sep-2022
https://doi.org/10.3390/informatics9040072
Soavi MZeni NMylopoulos JMich L(2022)From Legal Contracts to Formal Specifications: A Systematic Literature ReviewSN Computer Science10.1007/s42979-022-01228-43:5Online publication date: 21-Jun-2022
https://doi.org/10.1007/s42979-022-01228-4
Singh NGunjan VZurada JSingh NGunjan VZurada J(2022)Domain ModelingCognitive Tutor10.1007/978-981-19-5197-8_2(31-50)Online publication date: 18-Sep-2022
https://doi.org/10.1007/978-981-19-5197-8_2
Iyer VSanagavarapu LRaghu Reddy Y(2022)A Framework for Syntactic and Semantic Quality Evaluation of OntologiesSecure Knowledge Management In The Artificial Intelligence Era10.1007/978-3-030-97532-6_5(73-93)Online publication date: 23-Feb-2022
https://doi.org/10.1007/978-3-030-97532-6_5
Nazaruka EOsis JGriberman V(2020)Using Stanford CoreNLP Capabilities for Semantic Information Extraction from Textual DescriptionsEvaluation of Novel Approaches to Software Engineering10.1007/978-3-030-40223-5_1(1-21)Online publication date: 9-Feb-2020
https://doi.org/10.1007/978-3-030-40223-5_1
Nazaruka EOsis JGribermane V(2019)Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural LanguageApplied Computer Systems10.2478/acss-2019-001224:2(94-103)Online publication date: 1-Dec-2019
https://dl.acm.org/doi/10.2478/acss-2019-0012
de Araujo DRigo SBarbosa J(2017)Ontology-based information extraction for juridical events with case studies in Brazilian legal realmArtificial Intelligence and Law10.1007/s10506-017-9203-z25:4(379-396)Online publication date: 24-Jul-2017
https://doi.org/10.1007/s10506-017-9203-z
Araujo DRigo SMuller CChishman R(2013)Automatic Information Extraction from Texts with Inference and Linguistic Knowledge Acquisition RulesProceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) - Volume 0310.1109/WI-IAT.2013.171(151-154)Online publication date: 17-Nov-2013
https://dl.acm.org/doi/10.1109/WI-IAT.2013.171
Jlaiel NAissa RBen Ahmed M(2013)MetaProPOS++Proceedings of the First International Conference on Mining Intelligence and Knowledge Exploration - Volume 828410.1007/978-3-319-03844-5_68(695-708)Online publication date: 18-Dec-2013
https://dl.acm.org/doi/10.1007/978-3-319-03844-5_68
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