Hugging Face's logo

Datasets:
polyglot_ner

Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Arabic
Bulgarian
Catalan
Multilinguality:
multilingual
Size Categories:
unknown
Language Creators:
found
Annotations Creators:
machine-generated
Source Datasets:
original
ArXiv:
Tags:
License:
Dataset card Viewer Files Community
3
system HF staff commited on
Commit
ba1ca81
•
0 Parent(s):

Update files from the datasets library (from 1.0.2)

Browse files

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.2

Files changed (44) hide show
  1. .gitattributes +27 -0
  2. dataset_infos.json +1 -0
  3. dummy/ar/1.0.0/dummy_data.zip +3 -0
  4. dummy/bg/1.0.0/dummy_data.zip +3 -0
  5. dummy/ca/1.0.0/dummy_data.zip +3 -0
  6. dummy/combined/1.0.0/dummy_data.zip +3 -0
  7. dummy/cs/1.0.0/dummy_data.zip +3 -0
  8. dummy/da/1.0.0/dummy_data.zip +3 -0
  9. dummy/de/1.0.0/dummy_data.zip +3 -0
  10. dummy/el/1.0.0/dummy_data.zip +3 -0
  11. dummy/en/1.0.0/dummy_data.zip +3 -0
  12. dummy/es/1.0.0/dummy_data.zip +3 -0
  13. dummy/et/1.0.0/dummy_data.zip +3 -0
  14. dummy/fa/1.0.0/dummy_data.zip +3 -0
  15. dummy/fi/1.0.0/dummy_data.zip +3 -0
  16. dummy/fr/1.0.0/dummy_data.zip +3 -0
  17. dummy/he/1.0.0/dummy_data.zip +3 -0
  18. dummy/hi/1.0.0/dummy_data.zip +3 -0
  19. dummy/hr/1.0.0/dummy_data.zip +3 -0
  20. dummy/hu/1.0.0/dummy_data.zip +3 -0
  21. dummy/id/1.0.0/dummy_data.zip +3 -0
  22. dummy/it/1.0.0/dummy_data.zip +3 -0
  23. dummy/ja/1.0.0/dummy_data.zip +3 -0
  24. dummy/ko/1.0.0/dummy_data.zip +3 -0
  25. dummy/lt/1.0.0/dummy_data.zip +3 -0
  26. dummy/lv/1.0.0/dummy_data.zip +3 -0
  27. dummy/ms/1.0.0/dummy_data.zip +3 -0
  28. dummy/nl/1.0.0/dummy_data.zip +3 -0
  29. dummy/no/1.0.0/dummy_data.zip +3 -0
  30. dummy/pl/1.0.0/dummy_data.zip +3 -0
  31. dummy/pt/1.0.0/dummy_data.zip +3 -0
  32. dummy/ro/1.0.0/dummy_data.zip +3 -0
  33. dummy/ru/1.0.0/dummy_data.zip +3 -0
  34. dummy/sk/1.0.0/dummy_data.zip +3 -0
  35. dummy/sl/1.0.0/dummy_data.zip +3 -0
  36. dummy/sr/1.0.0/dummy_data.zip +3 -0
  37. dummy/sv/1.0.0/dummy_data.zip +3 -0
  38. dummy/th/1.0.0/dummy_data.zip +3 -0
  39. dummy/tl/1.0.0/dummy_data.zip +3 -0
  40. dummy/tr/1.0.0/dummy_data.zip +3 -0
  41. dummy/uk/1.0.0/dummy_data.zip +3 -0
  42. dummy/vi/1.0.0/dummy_data.zip +3 -0
  43. dummy/zh/1.0.0/dummy_data.zip +3 -0
  44. polyglot_ner.py +188 -0
.gitattributes ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.bin.* filter=lfs diff=lfs merge=lfs -text
5
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
6
+ *.ftz filter=lfs diff=lfs merge=lfs -text
7
+ *.gz filter=lfs diff=lfs merge=lfs -text
8
+ *.h5 filter=lfs diff=lfs merge=lfs -text
9
+ *.joblib filter=lfs diff=lfs merge=lfs -text
10
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
11
+ *.model filter=lfs diff=lfs merge=lfs -text
12
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
13
+ *.onnx filter=lfs diff=lfs merge=lfs -text
14
+ *.ot filter=lfs diff=lfs merge=lfs -text
15
+ *.parquet filter=lfs diff=lfs merge=lfs -text
16
+ *.pb filter=lfs diff=lfs merge=lfs -text
17
+ *.pt filter=lfs diff=lfs merge=lfs -text
18
+ *.pth filter=lfs diff=lfs merge=lfs -text
19
+ *.rar filter=lfs diff=lfs merge=lfs -text
20
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
21
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
22
+ *.tflite filter=lfs diff=lfs merge=lfs -text
23
+ *.tgz filter=lfs diff=lfs merge=lfs -text
24
+ *.xz filter=lfs diff=lfs merge=lfs -text
25
+ *.zip filter=lfs diff=lfs merge=lfs -text
26
+ *.zstandard filter=lfs diff=lfs merge=lfs -text
27
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
dataset_infos.json ADDED
@@ -0,0 +1 @@
 
1
+ {"ca": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ca", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 143746026, "num_examples": 372665, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 143746026, "size_in_bytes": 1250764632}, "de": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "de", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 156744752, "num_examples": 547578, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 156744752, "size_in_bytes": 1263763358}, "es": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "es", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 145387551, "num_examples": 386699, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 145387551, "size_in_bytes": 1252406157}, "fi": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "fi", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 95175890, "num_examples": 387465, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 95175890, "size_in_bytes": 1202194496}, "hi": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "hi", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 177698330, "num_examples": 401648, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 177698330, "size_in_bytes": 1284716936}, "id": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "id", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 152560050, "num_examples": 463862, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 152560050, "size_in_bytes": 1259578656}, "ko": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ko", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 174523416, "num_examples": 560105, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 174523416, "size_in_bytes": 1281542022}, "ms": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ms", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 155268778, "num_examples": 528181, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 155268778, "size_in_bytes": 1262287384}, "pl": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "pl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 159684112, "num_examples": 623267, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 159684112, "size_in_bytes": 1266702718}, "ru": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ru", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 200717423, "num_examples": 551770, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 200717423, "size_in_bytes": 1307736029}, "sr": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "sr", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 183437513, "num_examples": 559423, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 183437513, "size_in_bytes": 1290456119}, "tl": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "tl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 47104871, "num_examples": 160750, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 47104871, "size_in_bytes": 1154123477}, "vi": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "vi", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 141062258, "num_examples": 351643, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 141062258, "size_in_bytes": 1248080864}, "ar": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ar", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 183551222, "num_examples": 339109, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 183551222, "size_in_bytes": 1290569828}, "cs": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "cs", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 156792129, "num_examples": 564462, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 156792129, "size_in_bytes": 1263810735}, "el": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "el", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 195456401, "num_examples": 446052, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 195456401, "size_in_bytes": 1302475007}, "et": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "et", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 21961619, "num_examples": 87023, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 21961619, "size_in_bytes": 1128980225}, "fr": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "fr", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 147560734, "num_examples": 418411, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 147560734, "size_in_bytes": 1254579340}, "hr": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "hr", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 154151689, "num_examples": 629667, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 154151689, "size_in_bytes": 1261170295}, "it": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "it", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 147520094, "num_examples": 378325, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 147520094, "size_in_bytes": 1254538700}, "lt": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "lt", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 165319919, "num_examples": 848018, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 165319919, "size_in_bytes": 1272338525}, "nl": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "nl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 150737871, "num_examples": 520664, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 150737871, "size_in_bytes": 1257756477}, "pt": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "pt", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 145627857, "num_examples": 396773, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 145627857, "size_in_bytes": 1252646463}, "sk": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "sk", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 134174889, "num_examples": 500135, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 134174889, "size_in_bytes": 1241193495}, "sv": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "sv", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 157058369, "num_examples": 634881, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 157058369, "size_in_bytes": 1264076975}, "tr": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "tr", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 164456506, "num_examples": 607324, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 164456506, "size_in_bytes": 1271475112}, "zh": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "zh", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 165056969, "num_examples": 1570853, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 165056969, "size_in_bytes": 1272075575}, "bg": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "bg", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 190509195, "num_examples": 559694, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 190509195, "size_in_bytes": 1297527801}, "da": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "da", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 150551293, "num_examples": 546440, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 150551293, "size_in_bytes": 1257569899}, "en": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "en", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 145491677, "num_examples": 423982, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 145491677, "size_in_bytes": 1252510283}, "fa": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "fa", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 180093656, "num_examples": 492903, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 180093656, "size_in_bytes": 1287112262}, "he": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "he", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 177231613, "num_examples": 459933, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 177231613, "size_in_bytes": 1284250219}, "hu": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "hu", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 160702240, "num_examples": 590218, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 160702240, "size_in_bytes": 1267720846}, "ja": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ja", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 193679570, "num_examples": 1691018, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 193679570, "size_in_bytes": 1300698176}, "lv": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "lv", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 76256241, "num_examples": 331568, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 76256241, "size_in_bytes": 1183274847}, "no": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "no", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 152431612, "num_examples": 552176, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 152431612, "size_in_bytes": 1259450218}, "ro": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ro", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 96369897, "num_examples": 285985, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 96369897, "size_in_bytes": 1203388503}, "sl": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "sl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 148140079, "num_examples": 521251, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 148140079, "size_in_bytes": 1255158685}, "th": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "th", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 360409343, "num_examples": 217631, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 360409343, "size_in_bytes": 1467427949}, "uk": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "uk", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 198251631, "num_examples": 561373, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 198251631, "size_in_bytes": 1305270237}, "combined": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "combined", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 6286855097, "num_examples": 21070925, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 6286855097, "size_in_bytes": 7393873703}}
dummy/ar/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4e18049350c156e2044b0ab363af688eed81edf6b1363e38ed815b4526579118
3
+ size 1809
dummy/bg/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d6c0ff3413353fd23c29f94e352367616b593e67f7e2ab036be3387b4c6e72cb
3
+ size 1857
dummy/ca/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b98c10de419fdaa37551a25afcd8ad51f601e623521c0e47379e0f88a5b427ef
3
+ size 1605
dummy/combined/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4e33e129c16bda508c6ed2a850cc761d5247fa88add89f630e730571077f8e5c
3
+ size 56567
dummy/cs/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:036216dbeefb48f52209df19b3146fe72cb9668715f258417938eed0dd26c151
3
+ size 1742
dummy/da/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cb58b321b5688b07f7efddaed3416d81b1b195e6b1b642acadb59f7d7a24c40c
3
+ size 1674
dummy/de/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34f42efcbdd74b3eeff276863eba40dc88c43b9a65fdd996a385dadfab33d96b
3
+ size 1712
dummy/el/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:36b7b6dfb6d7303c0a29545e8f38729b9f51690300237e61a869567304e30fa0
3
+ size 1931
dummy/en/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c97447adecaa9fc7d1e55cea19f7fe5ef27eb1b16bf3031cb38fbebc058cf327
3
+ size 1657
dummy/es/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8eb85505f0c7a93606af35cbfdbda527208e5377f05b1045fec113c88c1f2df1
3
+ size 1582
dummy/et/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b13bb0b89db183718f51a148b536537efa507bc2c001e74cf6cb978beecdc2a2
3
+ size 1776
dummy/fa/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:044bd66827bc1647e66de628f096cdad93f50bffdf89f9bddad5347b767f652a
3
+ size 1653
dummy/fi/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d0c296e499df03a10e30f5e9653387270d48e34f027902051b4159efa38117c4
3
+ size 1858
dummy/fr/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:001627b73d97fd84ab65d989aacf73b576a8d5e0b164920821f22b4ee5711db2
3
+ size 1667
dummy/he/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e682cf9ea0358ef835bc795db1f373eb7636e623d672153745bee04aacfdd2c6
3
+ size 1724
dummy/hi/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:32afedb806b6cec6ddc23960094a115d42c7feedd2272feddeee6867dd529720
3
+ size 1809
dummy/hr/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7fe466c31efd4f38cab95b62569a103d80ce4636b27d88db02127f6ced7a3352
3
+ size 1680
dummy/hu/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d8645a8d5826ce9ec42ee6973c58b91762c51e0c7d5bc2861de24a9d6f0d071b
3
+ size 1814
dummy/id/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:432b60369eae7e030bd0b6860ceb71feaa80a6548cc4f30eac37659618ee711b
3
+ size 1695
dummy/it/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3386b9bcaa70cc7ed7056cfa9226a030dabd42bbe708a75b124f8964edca7ed
3
+ size 1620
dummy/ja/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3fb8bc8a80e6f4f72d9da7aafce7ac35b279270755d7658062bf843907daacf7
3
+ size 1806
dummy/ko/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3fa1d8d1e9bed7a41ca7e30e772da3335ad1f7f2a7ea5ef66764324bb60cca6
3
+ size 1896
dummy/lt/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:42bc2dc337fe01a688154110d3b6fb5e2bde0b996c1cd399694a7a07beac1972
3
+ size 1714
dummy/lv/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:be1c17af790fce1a27a573f6c2c19c835adfbe11ddb3791331236d0abc13a4f4
3
+ size 1756
dummy/ms/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d5a78791990ee4192e29a68b4554399abaa2c3b7cabf3e70a6e88620a163dfba
3
+ size 1679
dummy/nl/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:63f6a4aa760ae6f3ab873fa759b51226827154ea2ad8fa0693fd86597d0d1c2f
3
+ size 1671
dummy/no/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8734a455eec1409d151c052aa45fec16f0210ecaa10604627faab9cf8c1f4b2f
3
+ size 1715
dummy/pl/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d0742d10f8c0adfd3da8d7c6d1089aad849714ac290fcbcf67330a901375cbe5
3
+ size 1806
dummy/pt/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:071f5740f1006eaab49619f39b59c61db74558d477f4babec194c266aabbc083
3
+ size 1638
dummy/ro/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ebd32ba9b60585d99f30e0c3695da0a3e5cb5b989350c6613af7cbfc3c9d9edd
3
+ size 1700
dummy/ru/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ef2e49bda94147ef7d6d95e7d13975dddfc16ff3c83129121d16c11ee3a6088
3
+ size 1994
dummy/sk/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2404fa4332930687295d7b383f7e127ef4d6bf4bcf798f202f6c5965f77ffb64
3
+ size 1743
dummy/sl/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d452f00bbf5b67c8c6ae211807474b777a6a681f460c07d2c0863e1186a8b200
3
+ size 1697
dummy/sr/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2a705a07988f4c79c4402d0cb98b684705d0acc3b62310b44a4a2c69c8f3d100
3
+ size 1710
dummy/sv/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dc7771fd2cc46ca708cecc5155a753b8f030f0fe3276965f6339065b38d4c89a
3
+ size 1694
dummy/th/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a6a26c711a96f63455627193d2cd29cc766ed4e4328f8cb0f9a666e77043a19a
3
+ size 2821
dummy/tl/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:06be1b87f7d4866c06fafe700b03411442011623dccd045312529430ec1e902c
3
+ size 1566
dummy/tr/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6d88bf972d02527b90bec9099c378b0c855cdc44ec4e4a3c4f2ae9887e71021b
3
+ size 1855
dummy/uk/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:10e9fea4407c8941ae4eef95e728bc2f3a9d8315a20bde92914a467309341427
3
+ size 1857
dummy/vi/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0bfb8c18d910022628bedf1534872d8109a060a1444c68171781631034c5a21c
3
+ size 1640
dummy/zh/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b760934083f230e0cfabfce29ce1b434ed53e2464da300465c8e67f4af5d10f7
3
+ size 1316
polyglot_ner.py ADDED
@@ -0,0 +1,188 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2020 HuggingFace Datasets Authors.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ # Lint as: python3
17
+ """The Polyglot-NER Dataset."""
18
+
19
+ from __future__ import absolute_import, division, print_function
20
+
21
+ import os
22
+
23
+ import datasets
24
+
25
+
26
+ _CITATION = """\
27
+ @article{polyglotner,
28
+ author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},
29
+ title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},
30
+ journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},
31
+ month = {April},
32
+ year = {2015},
33
+ publisher = {SIAM},
34
+ }
35
+ """
36
+
37
+ _LANGUAGES = [
38
+ "ca",
39
+ "de",
40
+ "es",
41
+ "fi",
42
+ "hi",
43
+ "id",
44
+ "ko",
45
+ "ms",
46
+ "pl",
47
+ "ru",
48
+ "sr",
49
+ "tl",
50
+ "vi",
51
+ "ar",
52
+ "cs",
53
+ "el",
54
+ "et",
55
+ "fr",
56
+ "hr",
57
+ "it",
58
+ "lt",
59
+ "nl",
60
+ "pt",
61
+ "sk",
62
+ "sv",
63
+ "tr",
64
+ "zh",
65
+ "bg",
66
+ "da",
67
+ "en",
68
+ "fa",
69
+ "he",
70
+ "hu",
71
+ "ja",
72
+ "lv",
73
+ "no",
74
+ "ro",
75
+ "sl",
76
+ "th",
77
+ "uk",
78
+ ]
79
+
80
+ _LANG_FILEPATHS = {
81
+ lang: os.path.join(
82
+ "acl_datasets",
83
+ lang,
84
+ "data" if lang != "zh" else "", # they're all lang/data/lang_wiki.conll except "zh"
85
+ f"{lang}_wiki.conll",
86
+ )
87
+ for lang in _LANGUAGES
88
+ }
89
+
90
+ _DESCRIPTION = """\
91
+ Polyglot-NER
92
+ A training dataset automatically generated from Wikipedia and Freebase the task
93
+ of named entity recognition. The dataset contains the basic Wikipedia based
94
+ training data for 40 languages we have (with coreference resolution) for the task of
95
+ named entity recognition. The details of the procedure of generating them is outlined in
96
+ Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
97
+ corresponding to a different language. For example, "es" includes only spanish examples.
98
+ """
99
+
100
+ _DATA_URL = "http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz"
101
+ _HOMEPAGE_URL = "https://sites.google.com/site/rmyeid/projects/polylgot-ner"
102
+ _VERSION = "1.0.0"
103
+
104
+
105
+ class PolyglotNERConfig(datasets.BuilderConfig):
106
+ def __init__(self, *args, languages=None, **kwargs):
107
+ super().__init__(*args, version=datasets.Version(_VERSION, ""), **kwargs)
108
+ self.languages = languages
109
+
110
+ @property
111
+ def filepaths(self):
112
+ return [_LANG_FILEPATHS[lang] for lang in self.languages]
113
+
114
+
115
+ class PolyglotNER(datasets.GeneratorBasedBuilder):
116
+ """The Polyglot-NER Dataset"""
117
+
118
+ BUILDER_CONFIGS = [
119
+ PolyglotNERConfig(name=lang, languages=[lang], description=f"Polyglot-NER examples in {lang}.")
120
+ for lang in _LANGUAGES
121
+ ] + [
122
+ PolyglotNERConfig(
123
+ name="combined", languages=_LANGUAGES, description=f"Complete Polyglot-NER dataset with all languages."
124
+ )
125
+ ]
126
+
127
+ def _info(self):
128
+ return datasets.DatasetInfo(
129
+ description=_DESCRIPTION,
130
+ features=datasets.Features(
131
+ {
132
+ "id": datasets.Value("string"),
133
+ "lang": datasets.Value("string"),
134
+ "words": datasets.Sequence(datasets.Value("string")),
135
+ "ner": datasets.Sequence(datasets.Value("string")),
136
+ }
137
+ ),
138
+ supervised_keys=None,
139
+ homepage=_HOMEPAGE_URL,
140
+ citation=_CITATION,
141
+ )
142
+
143
+ def _split_generators(self, dl_manager):
144
+ """Returns SplitGenerators."""
145
+ path = dl_manager.download_and_extract(_DATA_URL)
146
+
147
+ return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"datapath": path})]
148
+
149
+ def _generate_examples(self, datapath):
150
+ sentence_counter = 0
151
+ for filepath, lang in zip(self.config.filepaths, self.config.languages):
152
+ filepath = os.path.join(datapath, filepath)
153
+ with open(filepath, encoding="utf-8") as f:
154
+ current_words = []
155
+ current_ner = []
156
+ for row in f:
157
+ row = row.rstrip()
158
+ if row:
159
+ token, label = row.split("\t")
160
+ current_words.append(token)
161
+ current_ner.append(label)
162
+ else:
163
+ # New sentence
164
+ if not current_words:
165
+ # Consecutive empty lines will cause empty sentences
166
+ continue
167
+ assert len(current_words) == len(current_ner), "💔 between len of words & ner"
168
+ sentence = (
169
+ sentence_counter,
170
+ {
171
+ "id": str(sentence_counter),
172
+ "lang": lang,
173
+ "words": current_words,
174
+ "ner": current_ner,
175
+ },
176
+ )
177
+ sentence_counter += 1
178
+ current_words = []
179
+ current_ner = []
180
+ yield sentence
181
+ # Don't forget last sentence in dataset 🧐
182
+ if current_words:
183
+ yield sentence_counter, {
184
+ "id": str(sentence_counter),
185
+ "lang": lang,
186
+ "words": current_words,
187
+ "ner": current_ner,
188
+ }