| --- |
| license: cc-by-4.0 |
| task_categories: |
| - token-classification |
| language: |
| - bn |
| - zh |
| - de |
| - en |
| - es |
| - fa |
| - fr |
| - hi |
| - it |
| - pt |
| - sv |
| - uk |
| tags: |
| - multiconer |
| - ner |
| - multilingual |
| - named entity recognition |
| - fine-grained ner |
| size_categories: |
| - 100K<n<1M |
| --- |
| # Dataset Card for Multilingual Complex Named Entity Recognition (MultiCoNER) |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** https://multiconer.github.io |
| - **Repository:** |
| - **Paper:** |
| - **Leaderboard:** https://multiconer.github.io/results, https://codalab.lisn.upsaclay.fr/competitions/10025 |
| - **Point of Contact:** https://multiconer.github.io/organizers |
|
|
| ### Dataset Summary |
|
|
| The tagset of MultiCoNER is a fine-grained tagset. |
| The fine to coarse level mapping of the tags are as follows: |
|
|
| * Location (LOC) : Facility, OtherLOC, HumanSettlement, Station |
| * Creative Work (CW) : VisualWork, MusicalWork, WrittenWork, ArtWork, Software |
| * Group (GRP) : MusicalGRP, PublicCORP, PrivateCORP, AerospaceManufacturer, SportsGRP, CarManufacturer, ORG |
| * Person (PER) : Scientist, Artist, Athlete, Politician, Cleric, SportsManager, OtherPER |
| * Product (PROD) : Clothing, Vehicle, Food, Drink, OtherPROD |
| * Medical (MED) : Medication/Vaccine, MedicalProcedure, AnatomicalStructure, Symptom, Disease |
|
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|
|
|
| ### Supported Tasks and Leaderboards |
|
|
| The final leaderboard of the shared task is available <a href="https://multiconer.github.io/results" target="_blank">here</a>. |
|
|
| ### Languages |
| Supported languages are Bangla, Chinese, English, Spanish, Farsi, French, German, Hindi, Italian, Portuguese, Swedish, Ukrainian. |
|
|
| ## Dataset Structure |
| The dataset follows CoNLL format. |
|
|
| ### Data Instances |
|
|
| Here are some examples in different languages: |
|
|
| * Bangla: [লিটল মিক্স | MusicalGrp] এ যোগদানের আগে তিনি [পিৎজা হাট | ORG] এ ওয়েট্রেস হিসাবে কাজ করেছিলেন। |
| * Chinese: 它的纤维穿过 [锁骨 | AnatomicalStructure] 并沿颈部侧面倾斜向上和内侧. |
| * English: [wes anderson | Artist]'s film [the grand budapest hotel | VisualWork] opened the festival . |
| * Farsi: است] ناگویا |HumanSettlement] مرکزاین استان شهر |
| * French: l [amiral de coligny | Politician] réussit à s y glisser . |
| * German: in [frühgeborenes | Disease] führt dies zu [irds | Symptom] . |
| * Hindi: १७९६ में उन्हें [शाही स्वीडिश विज्ञान अकादमी | Facility] का सदस्य चुना गया। |
| * Italian: è conservato nel [rijksmuseum | Facility] di [amsterdam | HumanSettlement] . |
| * Portuguese: também é utilizado para se fazer [licor | Drink] e [vinhos | Drink]. |
| * Spanish: fue superado por el [aon center | Facility] de [los ángeles | HumanSettlement] . |
| * Swedish: [tom hamilton | Artist] amerikansk musiker basist i [aerosmith | MusicalGRP] . |
| * Ukrainian: назва альбому походить з роману « [кінець дитинства | WrittenWork] » англійського письменника [артура кларка | Artist] . |
|
|
| ### Data Fields |
|
|
| The data has two fields. One is the token and another is the label. Here is an example from the English data. |
|
|
| ``` |
| # id f5458a3a-cd23-4df4-8384-4e23fe33a66b domain=en |
| doris _ _ B-Artist |
| day _ _ I-Artist |
| included _ _ O |
| in _ _ O |
| the _ _ O |
| album _ _ O |
| billy _ _ B-MusicalWork |
| rose _ _ I-MusicalWork |
| 's _ _ I-MusicalWork |
| jumbo _ _ I-MusicalWork |
| ``` |
|
|
|
|
| ### Data Splits |
|
|
| Train, Dev, and Test splits are provided |
|
|
| ## Dataset Creation |
| TBD |
|
|
|
|
| ### Licensing Information |
| CC BY 4.0 |
|
|
| ### Citation Information |
| ``` |
| @inproceedings{multiconer2-report, |
| title={{SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)}}, |
| author={Fetahu, Besnik and Kar, Sudipta and Chen, Zhiyu and Rokhlenko, Oleg and Malmasi, Shervin}, |
| booktitle={Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)}, |
| year={2023}, |
| publisher={Association for Computational Linguistics}, |
| } |
| |
| @article{multiconer2-data, |
| title={{MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition}}, |
| author={Fetahu, Besnik and Chen, Zhiyu and Kar, Sudipta and Rokhlenko, Oleg and Malmasi, Shervin}, |
| year={2023}, |
| } |
| ``` |
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|
