HIPE-2022 Shared Task Named Entity Datasets
<p>HIPE-2022 datasets used for the <a href="https://hipe-eval.github.io/HIPE-2022/">HIPE 2022 shared task</a> on <strong>named entity recognition and classification (NERC) and entity linking (EL) in multilingual historical documents</strong>. </p> <p>HIPE-2022 datasets are based on six primary datasets assembled and prepared for the shared task. Primary datasets are composed of historical newspapers and classic commentaries covering ca. 200 years, feature several languages and different entity tag sets and annotation schemes. They originate from several European cultural heritage projects, from HIPE organizers’ previous research project, and from the previous HIPE-2020 campaign. Some are already published, others are released for the first time for HIPE-2022.</p> <p>The HIPE-2022 shared task assembles and prepares these primary datasets in HIPE-2022 release(s), which correspond to a single package composed of neatly structured and homogeneously formatted files.</p> <p>Primary datasets undergo the following preparation steps:</p> <ul> <li>conversion to the HIPE format (with correction of data inconsistencies and metadata consolidation);</li> <li>rearrangement or composition of train and dev splits.</li> </ul> <p>Please also refer to:</p> <ul> <li>HIPE-2022 shared task website: <a href="https://hipe-eval.github.io/HIPE-2022/">https://hipe-eval.github.io/HIPE-2022/</a></li> <li>HIPE-2022 data repository: <a href="https://github.com/hipe-eval/HIPE-2022-data">https://github.com/hipe-eval/HIPE-2022-data</a></li> </ul> <p>Here is an overview of the primary datasets:</p> <table> <tbody> <tr> <td> <p><strong>Dataset alias</strong></p> </td> <td> <p><strong>Readme</strong></p> </td> <td> <p><strong>Document type</strong></p> </td> <td> <p><strong>Languages</strong></p> </td> <td> <p><strong>Suitable for</strong></p> </td> <td> <p><strong>Project</strong></p> </td> </tr> <tr> <td> <p>hipe2020</p> </td> <td> <p><a href="https://github.com/hipe-eval/HIPE-2022-data/blob/pre-release/documentation/README-hipe2020.md">link</a></p> </td> <td> <p>historical newspapers</p> </td> <td> <p>de, fr, en</p> </td> <td> <p>NERC-Coarse, NERC-Fine, EL</p> </td> <td> <p><a href="https://impresso.github.io/CLEF-HIPE-2020">CLEF-HIPE-2020</a></p> </td> </tr> <tr> <td> <p>newseye</p> </td> <td> <p><a href="https://github.com/hipe-eval/HIPE-2022-data/blob/pre-release/documentation/README-newseye.md">link</a></p> </td> <td> <p>historical newspapers</p> </td> <td> <p>de, fi, fr, sv</p> </td> <td> <p>NERC-Coarse, NERC-Fine, EL</p> </td> <td> <p><a href="https://www.newseye.eu/">NewsEye</a></p> </td> </tr> <tr> <td> <p>sonar</p> </td> <td> <p>link</p> </td> <td> <p>historical newspapers</p> </td> <td> <p>de</p> </td> <td> <p>NERC-Coarse, EL</p> </td> <td> <p><a href="https://sonar.fh-potsdam.de/">SoNAR</a></p> </td> </tr> <tr> <td> <p>letemps</p> </td> <td> <p><a href="https://github.com/hipe-eval/HIPE-2022-data/blob/pre-release/documentation/README-letemps.md">link</a></p> </td> <td> <p>historical newspapers</p> </td> <td> <p>fr</p> </td> <td> <p>NERC-Coarse, NERC-Fine</p> </td> <td> <p>LeTemps</p> </td> </tr> <tr> <td> <p>topres19th</p> </td> <td> <p><a href="https://github.com/hipe-eval/HIPE-2022-data/blob/pre-release/documentation/README-topres19th.md">link</a></p> </td> <td> <p>historical newspapers</p> </td> <td> <p>en</p> </td> <td> <p>NERC-Coarse, EL</p> </td> <td> <p><a href="https://livingwithmachines.ac.uk/">Living with Machines</a></p> </td> </tr> <tr> <td> <p>ajmc</p> </td> <td> <p><a href="https://github.com/hipe-eval/HIPE-2022-data/blob/pre-release/documentation/README-ajmc.md">link</a></p> </td> <td> <p>classical commentaries</p> </td> <td> <p>de, fr, en</p> </td> <td> <p>NERC-Coarse, NERC-Fine, EL</p> </td> <td> <p><a href="https://mromanello.github.io/ajax-multi-commentary/">AjMC</a></p> </td> </tr> </tbody> </table> <p> </p> <p>The HIPE-2022 team expresses her greatest appreciation to the partnering projects, namely <a href="https://mromanello.github.io/ajax-multi-commentary/">AJMC</a>, <em><a href="https://impresso-project.ch/">impresso</a>, </em><a href="https://impresso.github.io/CLEF-HIPE-2020/">HIPE-2020</a>, <a href="https://livingwithmachines.ac.uk/"><em>Living with Machines</em></a>, <a href="https://www.newseye.eu/"><em>NewsEye</em></a>, and <a href="https://sonar.fh-potsdam.de/"><em>SoNAR</em></a>, for contributing their NE-annotated datasets (and hiding a part thereof for the time of the evaluation campaign).</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 12
- Reuse readiness
- 8
- Engagement
- 4