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Natural Language Annotations for the Semantic Web

by: Boris Katz, Jimmy Lin, and Dennis Quan

In: Proc. ODBASE 2002 (2002) .

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URL:	http://www.ai.mit.edu/people/jimmylin/publications/

Because the ultimate purpose of the Semantic Web is to help users locate, organize, and process information, we strongly believe that it should be grounded in the information access method humans are most comfortable with ---natural language. However, the Resource Description Framework RDF, the foundation of the Semantic Web, was designed to be easily processed by computers, not humans. To render RDF friendlier to humans, we propose to augment it with natural language annotations, or metadata written in everyday language. We argue that natural language annotations are not only intuitive and e.ective, but can also accelerate the pace with which the Semantic Web is being adopted. We demonstrate the use of natural language annotations from within Haystack, an end user Semantic Web platform that also serves as a testbed for our ideas. In addition to a prototype SemanticWeb question answering system, we describe other opportunities for marrying natural language and Semantic Web technology.

BibTeX record

@inproceedings{Katz:2002d,
  abstract = {Because the ultimate purpose of the Semantic Web is to help users locate, organize, and process information, we strongly believe that it should be grounded in the information access method humans are most comfortable with ---natural language. However, the Resource Description Framework (RDF), the foundation of the Semantic Web, was designed to be easily processed by computers, not humans. To render RDF friendlier to humans, we propose to augment it with natural language annotations, or metadata written in everyday language. We argue that natural language annotations are not only intuitive and e.ective, but can also accelerate the pace with which the Semantic Web is being adopted. We demonstrate the use of natural language annotations from within Haystack, an end user Semantic Web platform that also serves as a testbed for our ideas. In addition to a prototype SemanticWeb question answering system, we describe other opportunities for marrying natural language and Semantic Web technology.},
  added-at = {2007-12-14T02:41:25.000+0100},
  author = {Katz, Boris and Lin, Jimmy and Quan, Dennis},
  biburl = {http://www.bibsonomy.org/bibtex/2b7d79060ed5b6fc52c0a5bce05ff7835/diego_ma},
  booktitle = {Proc. ODBASE 2002},
  interhash = {5c95ed50eee5748d677a9981055db90c},
  intrahash = {b7d79060ed5b6fc52c0a5bce05ff7835},
  keywords = {question_answering semantic_web annotation},
  timestamp = {2007-12-14T02:41:25.000+0100},
  title = {Natural Language Annotations for the Semantic Web},
  url = {http://www.ai.mit.edu/people/jimmylin/publications/},
  year = 2002
}

Endnote record

%0 Conference Paper
%1 Katz:2002d
%A Katz, Boris
%A Lin, Jimmy
%A Quan, Dennis
%B Proc. ODBASE 2002
%D 2002
%K 
%T Natural Language Annotations for the Semantic Web
%U http://www.ai.mit.edu/people/jimmylin/publications/
%X Because the ultimate purpose of the Semantic Web is to help users locate, organize, and process information, we strongly believe that it should be grounded in the information access method humans are most comfortable with ---natural language. However, the Resource Description Framework (RDF), the foundation of the Semantic Web, was designed to be easily processed by computers, not humans. To render RDF friendlier to humans, we propose to augment it with natural language annotations, or metadata written in everyday language. We argue that natural language annotations are not only intuitive and e.ective, but can also accelerate the pace with which the Semantic Web is being adopted. We demonstrate the use of natural language annotations from within Haystack, an end user Semantic Web platform that also serves as a testbed for our ideas. In addition to a prototype SemanticWeb question answering system, we describe other opportunities for marrying natural language and Semantic Web technology.

BibSonomy :: publication ::

Natural Language Annotations for the Semantic Web

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Abstract

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Endnote record