@inproceedings{c5fc3524ed154b08934ab6e82cfd0dfa,
title = "Coreference Resolution in Latvian",
abstract = "Coreference resolution (CR) is a current problem in natural language processing (NLP) research and it is a key task in applications such as question answering, text summarization and information extraction for which text understanding is of crucial importance. This paper describes a work in progress for improving Latvian coreference resolution that includes further experiments with the rule based LVCoref system, enlarging existing coreference corpus and the first efforts to adapt machine learning methods. LVCoref system now reaches 58.0\% F-score using predicted mentions and 76.5\% F-score if gold entity mentions are used.",
keywords = "Coreference resolution, corpus, machine learning, rule based",
author = "Arturs Znotiņ{\v s}",
note = "Publisher Copyright: {\textcopyright} 2014 The Authors and IOS Press.; 6th International Conference on Human Language Technologies - The Baltic Perspective, Baltic HLT 2014 ; Conference date: 26-09-2014 Through 27-09-2014",
year = "2014",
doi = "10.3233/978-1-61499-442-8-153",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "153--160",
editor = "Andrius Utka and Gintare Grigonyte and Jurgita Kapociute-Dzikiene and Jurgita Vaicenoniene",
booktitle = "Human Language Technologies - The Baltic Perspective",
address = "Netherlands",
}