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