Off-Road LAF: Encoding and Processing Annotations in NLP Workflows

Emanuele Lapponi, Erik Velldal, Stephan Oepen, Rune Lain Knudsen

Abstract
The Linguistic Annotation Framework (LAF) provides an abstract data model for specifying interchange representations to ensure interoperability among different annotation formats. This paper describes an ongoing effort to adapt the LAF data model as the interchange representation in complex workflows as used in the Language Analysis Portal (LAP), an on-line and large-scale processing service that is developed as part of the Norwegian branch of the Common Language Resources and Technology Infrastructure (CLARIN) initiative. Unlike several related on-line processing environments, which predominantly instantiate a distributed architecture of web services, LAP achives scalability to potentially very large data volumes through integration with the Norwegian national e-Infrastructure, and in particular job sumission to a capacity compute cluster. This setup leads to tighter integration requirements and also calls for efficient, low-overhead communication of (intermediate) processing results with workflows. We meet these demands by coupling the LAF data model with a lean, non-redundant JSON-based interchange format and integration of an agile and performant NoSQL database, allowing parallel access from cluster nodes, as the central repository of linguistic annotation.
Anthology ID:
L14-1734
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
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Publisher:
European Language Resources Association (ELRA)
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Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/978_Paper.pdf
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Cite (ACL):
Emanuele Lapponi, Erik Velldal, Stephan Oepen, and Rune Lain Knudsen. 2014. Off-Road LAF: Encoding and Processing Annotations in NLP Workflows. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Off-Road LAF: Encoding and Processing Annotations in NLP Workflows (Lapponi et al., LREC 2014)
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http://www.lrec-conf.org/proceedings/lrec2014/pdf/978_Paper.pdf
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