Search Results for author: Ali Hürriyetoğlu

Found 20 papers, 3 papers with code

PROTEST-ER: Retraining BERT for Protest Event Extraction

no code implementations ACL (CASE) 2021 Tommaso Caselli, Osman Mutlu, Angelo Basile, Ali Hürriyetoğlu

We analyze the effect of further retraining BERT with different domain specific data as an unsupervised domain adaptation strategy for event extraction.

Event Extraction Unsupervised Domain Adaptation

Multilingual Protest News Detection - Shared Task 1, CASE 2021

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).

Benchmarking Decision Making +6

Extended Multilingual Protest News Detection -- Shared Task 1, CASE 2021 and 2022

no code implementations21 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.

Document Classification Event Detection +3

Zero-Shot Ranking Socio-Political Texts with Transformer Language Models to Reduce Close Reading Time

no code implementations17 Oct 2022 Kiymet Akdemir, Ali Hürriyetoğlu

We show that one can reduce the close reading time by taking some percentage of the ranked documents that the percentage depends on how much recall they want to achieve.

Global Contentious Politics Database (GLOCON) Annotation Manuals

no code implementations17 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.

Event Coreference Resolution for Contentious Politics Events

1 code implementation18 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.

coreference-resolution Event Coreference Resolution

Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021): Workshop and Shared Task Report

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.

Bias Detection Learning Word Embeddings +3

COVCOR20 at WNUT-2020 Task 2: An Attempt to Combine Deep Learning and Expert rules

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.

Task 2 text-classification +1

Extracting actionable information from microtexts

no code implementations1 Aug 2020 Ali Hürriyetoğlu

Our experience confirms previous work that states that a well-designed human intervention or contribution in design, realization, or evaluation of an information system either improves its performance or enables its realization.

Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-context Setting

no code implementations1 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.

Sentence Task 2

Automated Extraction of Socio-political Events from News (AESPEN): Workshop and Shared Task Report

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.

Event Extraction Sentence

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