Coreferential Relations in Basque: The Annotation Process

• Published in: Journal of psycholinguistic research Vol. 47; no. 2; pp. 325 - 342
• Main Authors: Ceberio, Klara, Aduriz, Itziar, Díaz de Ilarraza, Arantza, Garcia-Azkoaga, Ines
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-04-2018; Springer; Springer Nature B.V
• Subjects: Annotations; Basque language; Behavioral Science and Psychology; Cognitive Psychology; Computational Linguistics; Corpus linguistics; Foreign Countries; Grammar; Humans; Indo European Languages; Language; Language Patterns; Language Research; Languages; Linguistics; Morphology (Languages); Morphosyntax; Natural Language Processing; Pragmatics; Psycholinguistics; Psychology; Reference (Semantic); Spain; Syntax; Word sense disambiguation; Spain; Coreference; Coreferential relations; Coreferential tagging
• ISSN: 0090-6905; 1573-6555
• DOI: 10.1007/s10936-018-9559-6

In this paper we present the coreferential tagging of part of the EPEC Corpus of Basque. Although coreference is a pragmatic linguistic phenomenon highly dependent on the situational context, it shows some language-specific patterns that vary according to the features of each language. Due to the fact that Basque is not an Indo-European language, it differs considerably in grammar from the languages spoken in surrounding areas. We will explain these features and the decisions made in each case. After describing the criteria defined for coreferential tagging in Basque, the annotation process will be explained. Our annotation is based on a morphologically and syntactically annotated corpus that provides us with a manageable environment, in which the specific structures that are part of a reference chain can be more easily identified. A part of the corpus was tagged by two annotators who marked up the same text independently, and by another annotator that acted as judge, solving problems in case of disagreement. All this process has been automatized as a result of previous studies carried out in this field. The automatic detection of mentions (Soraluze et al., in: Proceedings of Konvens, 
2012
) has provided us with a better working environment, and given us the possibility to build a first significant corpus for a later computational treatment of automatic coreferential resolution.