cryptexcode commited on
Commit
9eec7d4
1 Parent(s): 629d59d

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +121 -0
README.md CHANGED
@@ -1,3 +1,124 @@
1
  ---
2
  license: cc-by-4.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
  license: cc-by-4.0
3
+ task_categories:
4
+ - token-classification
5
+ language:
6
+ - bn
7
+ - zh
8
+ - de
9
+ - en
10
+ - es
11
+ - fa
12
+ - fr
13
+ - hi
14
+ - it
15
+ - pt
16
+ - sv
17
+ - uk
18
+ tags:
19
+ - multiconer
20
+ - ner
21
+ - multilingual
22
+ - named entity recognition
23
+ - fine-grained ner
24
+ size_categories:
25
+ - 100K<n<1M
26
  ---
27
+ # Dataset Card for Dataset Name
28
+
29
+ ## Dataset Description
30
+
31
+ - **Homepage:** https://multiconer.github.io
32
+ - **Repository:**
33
+ - **Paper:**
34
+ - **Leaderboard:** https://multiconer.github.io/results, https://codalab.lisn.upsaclay.fr/competitions/10025
35
+ - **Point of Contact:** https://multiconer.github.io/organizers
36
+
37
+ ### Dataset Summary
38
+
39
+ The tagset of MultiCoNER is a fine-grained tagset.
40
+ The fine to coarse level mapping of the tags are as follows:
41
+
42
+ * Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
43
+ * Creative Work (CW) : VisualWork, MusicalWork, WrittenWork, ArtWork, Software
44
+ * Group (GRP) : MusicalGRP, PublicCORP, PrivateCORP, AerospaceManufacturer, SportsGRP, CarManufacturer, ORG
45
+ * Person (PER) : Scientist, Artist, Athlete, Politician, Cleric, SportsManager, OtherPER
46
+ * Product (PROD) : Clothing, Vehicle, Food, Drink, OtherPROD
47
+ * Medical (MED) : Medication/Vaccine, MedicalProcedure, AnatomicalStructure, Symptom, Disease
48
+
49
+
50
+
51
+ ### Supported Tasks and Leaderboards
52
+
53
+ The final leaderboard of the shared task is available <a href="https://multiconer.github.io/results" target="_blank">here</a>.
54
+
55
+ ### Languages
56
+ Supported languages are Bangla, Chinese, English, Spanish, Farsi, French, German, Hindi, Italian, Portuguese, Swedish, Ukrainian.
57
+
58
+ ## Dataset Structure
59
+ The dataset follows CoNLL format.
60
+
61
+ ### Data Instances
62
+
63
+ Here are some examples in different languages:
64
+
65
+ * Bangla: [লিটল মিক্স | MusicalGrp] এ যোগদানের আগে তিনি [পিৎজা হাট | ORG] এ ওয়েট্রেস হিসাবে কাজ করেছিলেন।
66
+ * Chinese: 它的纤维穿过 [锁骨 | AnatomicalStructure] 并沿颈部侧面倾斜向上和内侧.
67
+ * English: [wes anderson | Artist]'s film [the grand budapest hotel | VisualWork] opened the festival .
68
+ * Farsi: است] ناگویا |HumanSettlement] مرکزاین استان شهر
69
+ * French: l [amiral de coligny | Politician] réussit à s y glisser .
70
+ * German: in [frühgeborenes | Disease] führt dies zu [irds | Symptom] .
71
+ * Hindi: १७९६ में उन्हें [शाही स्वीडिश विज्ञान अकादमी | Facility] का सदस्य चुना गया।
72
+ * Italian: è conservato nel [rijksmuseum | Facility] di [amsterdam | HumanSettlement] .
73
+ * Portuguese: também é utilizado para se fazer [licor | Drink] e [vinhos | Drink].
74
+ * Spanish: fue superado por el [aon center | Facility] de [los ángeles | HumanSettlement] .
75
+ * Swedish: [tom hamilton | Artist] amerikansk musiker basist i [aerosmith | MusicalGRP] .
76
+ * Ukrainian: назва альбому походить з роману « [кінець дитинства | WrittenWork] » англійського письменника [артура кларка | Artist] .
77
+
78
+ ### Data Fields
79
+
80
+ The data has two fields. One is the token and another is the label. Here is an example from the English data.
81
+
82
+ ```
83
+ # id f5458a3a-cd23-4df4-8384-4e23fe33a66b domain=en
84
+ doris _ _ B-Artist
85
+ day _ _ I-Artist
86
+ included _ _ O
87
+ in _ _ O
88
+ the _ _ O
89
+ album _ _ O
90
+ billy _ _ B-MusicalWork
91
+ rose _ _ I-MusicalWork
92
+ 's _ _ I-MusicalWork
93
+ jumbo _ _ I-MusicalWork
94
+ ```
95
+
96
+
97
+ ### Data Splits
98
+
99
+ Train, Dev, and Test splits are provided
100
+
101
+ ## Dataset Creation
102
+ TBD
103
+
104
+
105
+ ### Licensing Information
106
+ CC BY 4.0
107
+
108
+ ### Citation Information
109
+ ```
110
+ @inproceedings{multiconer2-report,
111
+ title={{SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)}},
112
+ author={Fetahu, Besnik and Kar, Sudipta and Chen, Zhiyu and Rokhlenko, Oleg and Malmasi, Shervin},
113
+ booktitle={Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)},
114
+ year={2023},
115
+ publisher={Association for Computational Linguistics},
116
+ }
117
+
118
+ @article{multiconer2-data,
119
+ title={{MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition}},
120
+ author={Fetahu, Besnik and Chen, Zhiyu and Kar, Sudipta and Rokhlenko, Oleg and Malmasi, Shervin},
121
+ year={2023},
122
+ }
123
+ ```
124
+