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ATLAS: A Flexible and Extensible Architecture for Linguistic Annotation

Published

Author(s)

S Bird, D Day, John S. Garofolo, J Henderson, Christophe Laprun, M Liberman

Abstract

We describe a formal model for annotating linguistic artifacts, from which we derive an application programming interface (API) to a suite of tools for manipulating these annotations. The abstract logical model provides for a range of storage formats and promotes the reuse of tools that interact through this API. We focus first on Annotation Graphs, a graph model for annotations on linear signals (such as text and speech) indexed by intervals, for which efficient database storage and querying techniques are applicable. We note how a wide range of existing annotated corpora can be mapped to this annotation graph model. This model is then generalized to encompass a wider variety of linguistic signals including both naturally occurring phenomena (as recorded images, video, multi-modal interactions, etc.) as well as the derived resources that are increasingly important to the engineering of natural language processing systems (such as word lists, dictionaries, aligned bilingual corpora, etc.). We conclude with a review of the current efforts towards implementing key pieces of this architecture.
Proceedings Title
International Conference on Language Resources and Evaluation | 2nd | | European Language Resources and Evaluation
Volume
3
Conference Dates
May 1, 2000
Conference Location
Athens, 1, GR
Conference Title
International Conference on Language Resources and Evaluation

Keywords

annotation, API, architecture, graphs, linguistic, query, reuse, signals

Citation

Bird, S. , Day, D. , Garofolo, J. , Henderson, J. , Laprun, C. and Liberman, M. (2000), ATLAS: A Flexible and Extensible Architecture for Linguistic Annotation, International Conference on Language Resources and Evaluation | 2nd | | European Language Resources and Evaluation, Athens, 1, GR, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=151499 (Accessed June 22, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created April 30, 2000, Updated October 12, 2021