Header

UZH-Logo

Maintenance Infos

Multilayer annotations in Parmenides


Rinaldi, Fabio; Dowdall, J; Hess, M; Elleman, J; Zarri, G P; Persidis, A; Bernard, L; Karanikas, H (2003). Multilayer annotations in Parmenides. In: K-CAP2003 workshop on, Sanibel, Florida, USA, October 2003 - October 2003.

Abstract

Most of the thrust in the semantic web movement comes from the observation that existing NLP tools are not sophisticated or efficient enough to process the full richness of Natural Language, and therefore Machine Understandable annotations need to be added to Web Resources in order to make them accessible by remote agents. However, when the target application is not required to handle a huge amount of documents, but more limited sets, it is conceivable and practical to take advantage of NLP tools to pre-process textual documents in order to generate annotations (to be verified by human editors).

We discuss an approach based on a combination of various Natural Language Processing techniques that addresses this issue. Documents are analized fully automatically and converted into a semantic annotation, which can then be stored together with the original documents. It is this annotation that constitutes the machine understandable resource that remote agents can query.

Abstract

Most of the thrust in the semantic web movement comes from the observation that existing NLP tools are not sophisticated or efficient enough to process the full richness of Natural Language, and therefore Machine Understandable annotations need to be added to Web Resources in order to make them accessible by remote agents. However, when the target application is not required to handle a huge amount of documents, but more limited sets, it is conceivable and practical to take advantage of NLP tools to pre-process textual documents in order to generate annotations (to be verified by human editors).

We discuss an approach based on a combination of various Natural Language Processing techniques that addresses this issue. Documents are analized fully automatically and converted into a semantic annotation, which can then be stored together with the original documents. It is this annotation that constitutes the machine understandable resource that remote agents can query.

Statistics

Downloads

81 downloads since deposited on 30 Jul 2009
14 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:October 2003
Deposited On:30 Jul 2009 10:05
Last Modified:06 Jun 2017 10:54

Download

Preview Icon on Download
Preview
Filetype: PDF
Size: 534kB

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations