Artificial Intelligence

NLSeminar- Linguistic Linked Open Data. Linking Corpora

When:
Friday, November 02, 2012, 3:00pm - 4:00pm PSTiCal
Where:
11th Floor Conf. Room (#1135)
Speaker:
Christian Chiarcos
Description:

Abstract:

Recent community efforts to create a Linked Open Data cloud of linguistic resources, in particular, a representation formalism for corpora in RDF/OWL, linking with terminology repositories for linguistic annotation and meta data, with lexical-semantic resources, and how SPARQL allows to query over everything.

In the last 15 years, the interoperability of language resources has been recognized as a major problem in the development of NLP infrastructures -- partly due to an increased focus on novel, underresourced languages and efforts to bootstrap language resources by annotation projection -- partly due to the increased interest in more abstract levels of linguistic analysis beyond morphosyntax and syntax, namely semantics, reference and discourse.

This talk describes the application of Semantic Web formalisms, RDF, OWL/DL and SPARQL, to facilitate the interoperability of linguistic corpora and linguistic annotations. Interoperability of linguistic corpora involves two aspects: Structural interoperability (annotations of different origin are represented using the same formalism) and conceptual interoperability (annotations of different origin are linked to a common vocabulary). I will describe ontology-based approaches for both aspects, the POWLA ontology that defines a data model for annotated corpora, and the Ontologies of Linguistic Annotation (OLiA) that provide definitions for linguistic categories and properties (Chiarcos 2012). As compared to state-of-the-art approaches based on standoff XML, e.g., the recently published ISO standard for an Linguistic Annotation Framework, key advantages of this approach include the existence of a rich technological ecosystem developed around RDF and OWL, including standardized query languages for directed acyclic (multi-) graphs (SPARQL), APIs, data base implementations, as well as the availability of OWL reasoners that can be applied to validate the consistency of linguistic corpora and their annotations and to infer additional information that is relevant, for example, for their appropriate visualization.

Naturally, representing corpora in OWL and RDF also allows to interlink resources freely, e.g., different annotation layers of a multi-layer corpus, translated texts in parallel corpora, or linguistic corpora and lexical-semantic resources. Modeled in this way, corpora can be fully integrated in a Linked Open Data (sub-)cloud of linguistic resources, along with lexical-semantic resources and knowledge bases of information about languages and linguistic terminology. The second part of my talk will introduce recent efforts to create a Linked Open Data sub-cloud of linguistic resources, the Linguistic Linked Open Data cloud (Chiarcos et al. 2012, cf.

http://linguistics.okfn.org).

References

Christian Chiarcos, Sebastian Hellmann, Sebastian Nordhoff, et al.

(2012), The Open Linguistics Working Group, Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC-2012). Istanbul, Turkey, May 2012.

[http://www.lrec-conf.org/proceedings/lrec2012/pdf/912_Paper.pdf]

Christian Chiarcos (2012), Interoperability of Corpora and Annotations, In: Christian Chiarcos, Sebastian Nordhoff, and Sebastian Hellmann (eds.) Linked Data in Linguistics. Representing and Connecting Language Data and Language Metadata. Springer, Heidelberg.

[http://www.springer.com/computer/ai/book/978-3-642-28248-5]

Bio

Christian Chiarcos studied Computer Science and General Linguistics at the Technical University Berlin, Germany, and received his PhD in Computational Linguistics from the University of Potsdam, Germany in 2010. He is currently affiliated with the University of Frankfurt/M., Germany. Since April 2012, he is visiting scholar at the ISI. His primary areas of expertese include the study and modeling of discourse semantics, as well as the development of infrastructures for rich and heterogeneous linguistic annotations.

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