Quotations, Coreference Resolution, and Sentiment Annotations in Croatian News Articles: An Exploratory Study

TL;DR

This study introduces a Croatian news corpus annotated for direct-speech extraction, co-reference resolution, and sentiment analysis, highlighting language-specific challenges and providing a resource for NLP tasks.

Contribution

It presents a new annotated Croatian news corpus focusing on quotations, co-reference, and sentiment, with analysis of language-specific differences from English.

Findings

Identified language-specific annotation challenges

Created a Croatian annotated corpus for NLP tasks

Analyzed differences between Croatian and English annotations

Abstract

This paper presents a corpus annotated for the task of direct-speech extraction in Croatian. The paper focuses on the annotation of the quotation, co-reference resolution, and sentiment annotation in SETimes news corpus in Croatian and on the analysis of its language-specific differences compared to English. From this, a list of the phenomena that require special attention when performing these annotations is derived. The generated corpus with quotation features annotations can be used for multiple tasks in the field of Natural Language Processing.