Provenance for Linguistic Corpora Through Nanopublications

TL;DR

This paper introduces a nanopublication-based approach to improve the interoperability and provenance tracking of linguistic corpora, enabling more effective querying and integration of annotated data in computational linguistics.

Contribution

It presents a novel method for representing linguistic annotations as nanopublications, facilitating reliable linking, querying, and provenance tracking across multiple corpora.

Findings

Nanopublications enable interoperability of linguistic annotations.

SPARQL queries can extract data across multiple corpora effectively.

The approach improves data provenance and version control in linguistic resources.

Abstract

Research in Computational Linguistics is dependent on text corpora for training and testing new tools and methodologies. While there exists a plethora of annotated linguistic information, these corpora are often not interoperable without significant manual work. Moreover, these annotations might have evolved into different versions, making it challenging for researchers to know the data's provenance. This paper addresses this issue with a case study on event annotated corpora and by creating a new, more interoperable representation of this data in the form of nanopublications. We demonstrate how linguistic annotations from separate corpora can be reliably linked from the start, and thereby be accessed and queried as if they were a single dataset. We describe how such nanopublications can be created and demonstrate how SPARQL queries can be performed to extract interesting content from the new representations. The queries show that information of multiple corpora can be retrieved more easily and effectively because the information of different corpora is represented in a uniform data format.