Samia Touileb, Jeanett Murstad, Petter Mæhlum, Lubos Steskal, Lilja Charlotte Storset, Huiling You, Lilja Øvrelid
| Challenge: | EDEN is the first dataset annotated with event information at the sentence level for the Norwegian language. |
| Approach: | They propose to annotate Norwegian news text and transcribed speech using ACE event schema. |
| Outcome: | The proposed dataset is the first annotated dataset for Norwegian, with a language-specific annotation process. |
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A Fine-grained Sentiment Dataset for Norwegian (2020.lrec-1)
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| Challenge: | Using a dataset for fine-grained sentiment analysis in Norwegian, we examine the annotation effort and provide an overview of the developed annotation guidelines. |
| Approach: | They propose a dataset for fine-grained sentiment analysis in Norwegian . they provide an overview of the developed annotation guidelines and analyze inter-annotator agreement . |
| Outcome: | The proposed dataset is the first of its kind for Norwegian and is available online. |
MAVEN: A Massive General Domain Event Detection Dataset (2020.emnlp-main)
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Xiaozhi Wang, Ziqi Wang, Xu Han, Wangyi Jiang, Rong Han, Zhiyuan Liu, Juanzi Li, Peng Li, Yankai Lin, Jie Zhou
| Challenge: | Existing datasets exhibit data scarcity and limited coverage of general-domain events. |
| Approach: | They present a MAssive eVENt detection dataset which contains 4,480 Wikipedia documents and 168 event types. |
| Outcome: | The proposed dataset shows that existing methods cannot achieve promising results on the small datasets. |
NoReC: The Norwegian Review Corpus (L18-1)
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Erik Velldal, Lilja Øvrelid, Eivind Alexander Bergem, Cathrine Stadsnes, Samia Touileb, Fredrik Jørgensen
| Challenge: | The Norwegian Review Corpus is a dataset of full-text reviews from major news sources. |
| Approach: | This paper presents the Norwegian Review Corpus, created for document-level sentiment analysis. |
| Outcome: | The corpus comprises more than 35,000 full-text reviews from a range of different domains. |
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. |
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. |
| Outcome: | The proposed dataset has over 56,000+ events and 242,000+ arguments. |
A French Corpus for Event Detection on Twitter (2020.lrec-1)
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| Challenge: | Existing datasets may have different definitions of event or topic, which leads to inconsistent results. |
| Approach: | They present a corpus annotated for event detection tasks consisting of 38 million tweets in French and 130,000 manually annotating tweets as related or unrelated to a given event. |
| Outcome: | The proposed method performs best on 38 million tweets in French and another publicly available dataset of tweets. |
CrudeOilNews: An Annotated Crude Oil News Corpus for Event Extraction (2022.lrec-1)
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| Challenge: | a corpus of English crude oil news for event extraction is presented . the corpus contains 425 news articles with approximately 11k events annotated . |
| Approach: | They present a corpus of English Crude Oil news for event extraction . it is the first of its kind for Commodity News and contributes to text mining . |
| Outcome: | The proposed corpus of English crude oil news is the first of its kind for Commodity News . the annotated news articles are compared with the standard news articles . |
NorNE: Annotating Named Entities for Norwegian (2020.lrec-1)
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| Challenge: | Using the annotations of the existing treebank, we have created a dataset for named entity recognition for Norwegian. |
| Approach: | They propose to create a manually annotated corpus of named entities for Norwegian . they propose to add named entity annotations to existing treebank . |
| Outcome: | The proposed dataset extends the annotation of the existing Norwegian Dependency Treebank. |
Automatic Data Acquisition for Event Coreference Resolution (2021.eacl-main)
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| Challenge: | lexical paraphrases and high precision rules informed by news discourse structure can be used to collect coreferential and non-coreferential event pairs from unlabeled English news articles. |
| Approach: | They propose to use lexical paraphrases and news discourse structure to automatically collect coreferential and non-coreferential event pairs from unlabeled English news articles. |
| Outcome: | The proposed model performs better than the supervised model on evaluation datasets with different event domains and text genres. |
Treasures Outside Contexts: Improving Event Detection via Global Statistics (2021.emnlp-main)
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| Challenge: | Existing neural-based ED models are confused by changeable contexts during testing . we propose a system that extracts statistical event features from word-event cooccurrence frequencies . |
| Approach: | They propose to integrate a set of statistical event features from word-event co-occurrence frequencies into the training set to cooperate with contextual features. |
| Outcome: | The proposed model outperforms ten strong baselines on ACE2005 and KBP2015 datasets. |