# A Named Entity Recognition Dataset for Kazakh
- This is a modified version of the dataset provided in the [LREC 2022](https://lrec2022.lrec-conf.org/en/) paper [*KazNERD: Kazakh Named Entity Recognition Dataset*](https://aclanthology.org/2022.lrec-1.44).
- The original repository for the paper can be found at *https://github.com/IS2AI/KazNERD*.
- Tokens denoting speech disfluencies and hesitations (parenthesised) and background noise [bracketed] were removed.
- A total of 2,027 duplicate sentences were removed.
### Statistics for training (Train), validation (Valid), and test (Test) sets
| Unit | Train | Valid | Test | Total |
| :---: | :---: | :---: | :---: | :---: |
| Sentence | 88,540 (80.00%) | 11,067 (10.00%) | 11,068 (10.00%) | 110,675 (100%) |  
| Token | 1,088,461 (80.04%) | 136,021 (10.00%) | 135,426 (9.96%) | 1,359,908 (100%) | 
| NE | 106,148 (80.17%) | 13,189 (9.96%) | 13,072 (9.87%) | 132,409 (100%) |
### 80 / 10 / 10 split
|Representation| Train | Valid | Test | Total |
| :---: | :---: | :---: | :---: | :---: |
| **AID** | 67,582 (79.99%) | 8,439 (9.99%) | 8,467 (10.02%)| 84,488 (100%) |
| **BID** | 19,006 (80.11%) | 2,380 (10.03%) | 2,338 (9.85%)| 23,724 (100%) |
| **CID** | 1,050 (78.89%) | 138 (10.37%) | 143 ( 10.74%) | 1,331 (100%) |
| **DID** | 633 (79.22%) | 82 (10.26%) | 84 (10.51%) | 799 (100%) |
| **EID** | 260 (81.00%) | 27 (8.41%) | 34 (10.59%)| 321 (100%) |
| **FID** | 9 (75.00%) | 1 (8.33%)| 2 (16.67%)| 12 (100%) |
|**Total**| **88,540 (80.00%)** | **11,067 (10.00%)** | **11,068 (10.00%)** | **110,675 (100%)** |
### Distribution of representations across sets
|Representation| Train | Valid | Test | Total |
| :---: | :---: | :---: | :---: | :---: |
| **AID** | 67,582 (76.33%) | 8,439 (76.25%) | 8,467 (76.50%)| 84,488 (76.34%) |
| **BID** | 19,006 (21.47%) | 2,380 (21.51%) | 2,338 (21.12%)| 23,724 (21.44%) |
| **CID** | 1,050 (1.19%) | 138 (1.25%) | 143 ( 1.29%) | 1,331 (1.20%) |
| **DID** | 633 (0.71%) | 82 (0.74%) | 84 (0.76%) | 799 (0.72%) |
| **EID** | 260 (0.29%) | 27 (0.24%) | 34 (0.31%)| 321 (0.29%) |
| **FID** | 9 (0.01%) | 1 (0.01%)| 2 (0.02%)| 12 (0.01%) |
|**Total**| **88,540 (100.00%)** | **11,067 (10.00%)** | **11,068 (10.00%)** | **110,675 (100%)** |
###  Distribution of NEs across sets
| **NE Class** | **Train** | **Valid** | **Test** | **Total** |
|:---:| :---: | :---: | :---: | :---: |
| **ADAGE** | 153 (0.14%) | 19 (0.14%) | 17 (0.13%) | 189 (0.14%) |
| **ART** | 1,533 (1.44%) | 155 (1.18%) | 161 (1.23%) | 1,849 (1.40%) |
| **CARDINAL** | 23,135 (21.8%) | 2,878 (21.82%) | 2,789 (21.34%) | 28,802 (21.75%) |
| **CONTACT** | 159 (0.15%) | 18 (0.14%) | 20 (0.15%) | 197 (0.15%) |
| **DATE** | 20,006 (18.85%) | 2,603 (19.74%) | 2,584 (19.77%) | 25,193 (19.03%) |
| **DISEASE** | 1,022 (0.96%) | 121 (0.92%) | 119 (0.91%) | 1,262 (0.95%) |
| **EVENT** | 1,331 (1.25%) | 154 (1.17%) | 154 (1.18%) | 1,639 (1.24%) |
| **FACILITY** | 1,723 (1.62%) | 178 (1.35%) | 197 (1.51%) | 2,098 (1.58%) |
| **GPE** | 13,625 (12.84%) | 1,656 (12.56%) | 1,691 (12.94%) | 16,972 (12.82%) |
| **LANGUAGE** | 350 (0.33%) | 47 (0.36%) | 41 (0.31%) | 438 (0.33%) |
| **LAW** | 419 (0.39%) | 56 (0.42%) | 55 (0.42%) | 530 (0.40%) |
| **LOCATION** | 1,736 (1.64%) | 210 (1.59%) | 208 (1.59%) | 2,154 (1.63%) |
| **MISCELLANEOUS** | 191 (0.18%) | 26 (0.2%) | 26 (0.2%) | 243 (0.18%) |
| **MONEY** | 3,652 (3.44%) | 455 (3.45%) | 427 (3.27%) | 4,534 (3.42%) |
| **NON_HUMAN** | 6 (0.01%) | 1 (0.01%) | 1 (0.01%) | 8 (0.01%) |
| **NORP** | 2,929 (2.76%) | 374 (2.84%) | 368 (2.82%) | 3,671 (2.77%) |
| **ORDINAL** | 3,054 (2.88%) | 385 (2.92%) | 382 (2.92%) | 3,821 (2.89%) |
| **ORGANISATION** | 5,956 (5.61%) | 753 (5.71%) | 718 (5.49%) | 7,427 (5.61%) |
| **PERCENTAGE** | 3,357 (3.16%) | 437 (3.31%) | 462 (3.53%) | 4,256 (3.21%) |
| **PERSON** | 9,817 (9.25%) | 1,175 (8.91%) | 1,151 (8.81%) | 12,143 (9.17%) |
| **POSITION** | 4,844 (4.56%) | 587 (4.45%) | 597 (4.57%) | 6,028 (4.55%) |
| **PRODUCT** | 586 (0.55%) | 73 (0.55%) | 75 (0.57%) | 734 (0.55%) |
| **PROJECT** | 1,681 (1.58%) | 209 (1.58%) | 206 (1.58%) | 2,096 (1.58%) |
| **QUANTITY** | 3,063 (2.89%) | 411 (3.12%) | 403 (3.08%) | 3,877 (2.93%) |
| **TIME** | 1,820 (1.71%) | 208 (1.58%) | 220 (1.68%) | 2,248 (1.70%) |
| **Total** | **106,148 (100%)** | **13,189 (100%)** | **13,072 (100%)** | **132,409 (100%)** |
task_categories:token-classification task_ids:named-entity-recognition multilinguality:monolingual size_categories:100K<n<1M language:kk license:cc-by-4.0 region:us
{"language": ["kk"], "license": "cc-by-4.0", "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "pretty_name": "A Named Entity Recognition Dataset for Kazakh"}
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #multilinguality-monolingual #size_categories-100K<n<1M #language-Kazakh #license-cc-by-4.0 #region-us 

A Named Entity Recognition Dataset for Kazakh
=============================================


* This is a modified version of the dataset provided in the LREC 2022 paper *KazNERD: Kazakh Named Entity Recognition Dataset*.
* The original repository for the paper can be found at \*URL
* Tokens denoting speech disfluencies and hesitations (parenthesised) and background noise [bracketed] were removed.
* A total of 2,027 duplicate sentences were removed.


### Statistics for training (Train), validation (Valid), and test (Test) sets



### 80 / 10 / 10 split



### Distribution of representations across sets



### Distribution of NEs across sets




### Statistics for training (Train), validation (Valid), and test (Test) sets ### 80 / 10 / 10 split ### Distribution of representations across sets ### Distribution of NEs across sets
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #multilinguality-monolingual #size_categories-100K<n<1M #language-Kazakh #license-cc-by-4.0 #region-us 
 ### Statistics for training (Train), validation (Valid), and test (Test) sets ### 80 / 10 / 10 split ### Distribution of representations across sets ### Distribution of NEs across sets
passage: TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #multilinguality-monolingual #size_categories-100K<n<1M #language-Kazakh #license-cc-by-4.0 #region-us 
### Statistics for training (Train), validation (Valid), and test (Test) sets### 80 / 10 / 10 split### Distribution of representations across sets### Distribution of NEs across sets