Texts

DWIE

Deutsche Welle corpus for Information Extraction

Introduced in DWIE: an entity-centric dataset for multi-task document-level information extraction

About this Dataset

The 'Deutsche Welle corpus for Information Extraction' (DWIE) is a multi-task dataset that combines four main Information Extraction (IE) annotation sub-tasks: (i) Named Entity Recognition (NER), (ii) Coreference Resolution, (iii) Relation Extraction (RE), and (iv) Entity Linking. DWIE is conceived as an entity-centric dataset that describes interactions and properties of conceptual entities on the level of the complete document.

Source: https://arxiv.org/abs/2009.12626

Source: DWIE: an entity-centric dataset for multi-task document-level information extraction

Dataset Variants

DWIE

Papers1

DWIE: an entity-centric dataset for multi-task document-level information extraction

This paper proposes a new entity-driven metric that takes into account the number of mentions that compose each of the predicted and ground truth entities in DWIE, and proposes to use graph-based neural message passing techniques between document-level mention spans to stimulate further research in graph neural networks for representation learning in multi-task IE.

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Tasks

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Named Entity Recognition (NER)Relation Extraction Entity Linking Coreference Resolution Document-level Relation Extraction Document-level Closed Information Extraction

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