no code implementations • ACL (CASE) 2021 • Ali Hürriyetoğlu, Osman Mutlu, Erdem Yörük, Farhana Ferdousi Liza, Ritesh Kumar, Shyam Ratan
Task 1, which is the focus of this report, is on multilingual protest news detection and comprises four subtasks that are document classification (subtask 1), sentence classification (subtask 2), event sentence coreference identification (subtask 3), and event extraction (subtask 4).
no code implementations • 28 May 2024 • Ali Hürriyetoğlu, Osman Mutlu, Fırat Duruşan, Erdem Yörük
GLOCON is a database of contentious events automatically extracted from national news sources from various countries in multiple languages.
no code implementations • 2 Dec 2023 • Ali Hürriyetoğlu, Hristo Tanev, Osman Mutlu, Surendrabikram Thapa, Fiona Anting Tan, Erdem Yörük
We provide a summary of the sixth edition of the CASE workshop that is held in the scope of RANLP 2023.
no code implementations • 21 Nov 2022 • Ali Hürriyetoğlu, Osman Mutlu, Fırat Duruşan, Onur Uca, Alaeddin Selçuk Gürel, Benjamin Radford, Yaoyao Dai, Hansi Hettiarachchi, Niklas Stoehr, Tadashi Nomoto, Milena Slavcheva, Francielle Vargas, Aaqib Javid, Fatih Beyhan, Erdem Yörük
The CASE 2022 extension consists of expanding the test data with more data in previously available languages, namely, English, Hindi, Portuguese, and Spanish, and adding new test data in Mandarin, Turkish, and Urdu for Sub-task 1, document classification.
no code implementations • 21 Nov 2022 • Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella, Reyyan Yeniterzi, Osman Mutlu, Erdem Yörük
We provide a summary of the fifth edition of the CASE workshop that is held in the scope of EMNLP 2022.
no code implementations • 17 May 2022 • Fırat Duruşan, Ali Hürriyetoğlu, Erdem Yörük, Osman Mutlu, Çağrı Yoltar, Burak Gürel, Alvaro Comin
In order to assure these, the annotation manuals in this document lay out the rules according to which annotators code the news articles.
1 code implementation • 18 Mar 2022 • Ali Hürriyetoğlu, Osman Mutlu, Fatih Beyhan, Fırat Duruşan, Ali Safaya, Reyyan Yeniterzi, Erdem Yörük
We propose a dataset for event coreference resolution, which is based on random samples drawn from multiple sources, languages, and countries.
no code implementations • ACL (CASE) 2021 • Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella, Jakub Piskorski, Reyyan Yeniterzi, Erdem Yörük
This workshop is the fourth issue of a series of workshops on automatic extraction of socio-political events from news, organized by the Emerging Market Welfare Project, with the support of the Joint Research Centre of the European Commission and with contributions from many other prominent scholars in this field.
no code implementations • EMNLP (WNUT) 2020 • Ali Hürriyetoğlu, Ali Safaya, Nelleke Oostdijk, Osman Mutlu, Erdem Yörük
In the scope of WNUT-2020 Task 2, we developed various text classification systems, using deep learning models and one using linguistically informed rules.
1 code implementation • AKBC 2020 • Ali Hürriyetoğlu, Erdem Yörük, Deniz Yüret, Osman Mutlu, Çağrı Yoltar, Fırat Duruşan, Burak Gürel
For each news source, the annotation starts on random samples of news articles and continues with samples that are drawn using active learning.
no code implementations • 1 Aug 2020 • Ali Hürriyetoğlu, Erdem Yörük, Deniz Yüret, Çağrı Yoltar, Burak Gürel, Fırat Duruşan, Osman Mutlu, Arda Akdemir
We present an overview of the CLEF-2019 Lab ProtestNews on Extracting Protests from News in the context of generalizable natural language processing.
no code implementations • LREC 2020 • Ali Hürriyetoğlu, Vanni Zavarella, Hristo Tanev, Erdem Yörük, Ali Safaya, Osman Mutlu
The workshop attracted research papers related to evaluation of machine learning methodologies, language resources, material conflict forecasting, and a shared task participation report in the scope of socio-political event information collection.