Dataset Card for Multilingual Complex Named Entity Recognition (MultiCoNER)

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

Supported Tasks and Leaderboards

The final leaderboard of the shared task is available here .

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

Loading the Dataset

from datasets import load_dataset

english_data = load_dataset('MultiCoNER/multiconer_v2', 'English (EN)')

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},
}