| Challenge: | Using the Web, we propose a corpus for information extraction and text classification. |
| Approach: | They propose to use a corpus for information extraction and natural language processing (NLP) tasks such as text classification. |
| Outcome: | The proposed corpus can be used for information extraction and natural language processing tasks such as text classification. |
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Tanmay Parekh, Jeffrey Kwan, Jiarui Yu, Sparsh Johri, Hyosang Ahn, Sreya Muppalla, Kai-Wei Chang, Wei Wang, Nanyun Peng
| Challenge: | Prior studies focused on English posts to provide early warnings for epidemic prediction, but these work focused on non-English posts. |
| Approach: | They propose a multilingual event extraction framework for extracting epidemic event information for any disease and language using 5.1K tweets in four languages. |
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DEIE: Benchmarking Document-level Event Information Extraction with a Large-scale Chinese News Dataset (2024.lrec-main)
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| Challenge: | Existing event-based datasets mainly target sentence-level tasks . current models struggle with "document" annotation, a key feature of the current model . |
| Approach: | They propose a large-scale document-level event information extraction dataset with over 56,000+ events and 242,000+ arguments. |
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MEE: A Novel Multilingual Event Extraction Dataset (2022.emnlp-main)
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| Challenge: | Existing methods for Event Extraction are limited for non-English languages . lack of high-quality multilingual datasets has been the main hindrance . |
| Approach: | They propose a multilingual event extraction dataset that provides annotation for more than 50K event mentions in 8 typologically different languages. |
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Multilingual Epidemiological Text Classification: A Comparative Study (2020.coling-main)
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| Challenge: | a comparative study of multilingual text classification models analyzes the performance of different models based on different languages . low-resource languages are highly influenced by typology of the languages on which the models have been trained or fine-tuned but also by their size. |
| Approach: | They compare machine and deep learning models with a dataset of epidemiological news articles . they find that the performance of the models is proportionate to the training data size . |
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MUSIED: A Benchmark for Event Detection from Multi-Source Heterogeneous Informal Texts (2022.emnlp-main)
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| Challenge: | Recent efforts to classify unstructured texts into specific types have been limited in practical scenarios. |
| Approach: | They propose to use Chinese text conversations and phone conversations to expand event detection to the scenarios involving informal and heterogeneous texts. |
| Outcome: | The proposed dataset is based on user reviews, text conversations, and phone conversations in a leading e-commerce platform for food service. |
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence (2021.findings-acl)
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| Challenge: | a new corpus-level evaluation approach for event extraction is needed in social science applications . human annotations are often required to extract the actions of political actors and actors . a novel corpus evaluation approach can guide creation of similar social science-oriented resources . |
| Approach: | They propose a corpus-based approach to event extraction that integrates corpus evaluation with real-world social science . they use human annotations to read and label every document for mentions of police activity events . |
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PolyNarrative: A Multilingual, Multilabel, Multi-domain Dataset for Narrative Extraction from News Articles (2025.acl-long)
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Nikolaos Nikolaidis, Nicolas Stefanovitch, Purificação Silvano, Dimitar Iliyanov Dimitrov, Roman Yangarber, Nuno Guimarães, Elisa Sartori, Ion Androutsopoulos, Preslav Nakov, Giovanni Da San Martino, Jakub Piskorski
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Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling (2024.findings-emnlp)
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| Challenge: | Existing approaches for text-based event prediction are limited in quality due to dynamic nature of international relations and conflicting economic dynamics. |
| Approach: | They propose a novel dataset that leverages the advanced reasoning capabilities of large-language models to address these limitations. |
| Outcome: | The proposed dataset features high-quality scoring labels generated through advanced prompt modeling and rigorously validated by domain experts in political science. |
Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search (2023.acl-demo)
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| Challenge: | Using only English training data, ISI-Clear makes global events available on-demand in 100 languages . Using a fixed task, events may still shift from day to day . |
| Approach: | They propose a cross-lingual zero-shot event extraction system that makes global events available on-demand in 100 languages. |
| Outcome: | The proposed system can extract events from non-English documents in 100 languages. |
HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crises Response (2022.findings-emnlp)
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Selim Fekih, Nicolo’ Tamagnone, Benjamin Minixhofer, Ranjan Shrestha, Ximena Contla, Ewan Oglethorpe, Navid Rekabsaz
| Challenge: | During humanitarian crises, a quick and accurate analysis of relevant data is critical to a timely and effective response. |
| Approach: | They introduce and release a multilingual dataset of humanitarian response documents annotated by experts in the humanitarian response domain. |
| Outcome: | The proposed dataset provides documents in three languages and covers a variety of humanitarian crises from 2018 to 2021 across the globe. |