Update files from the datasets library (from 1.9.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.9.0

README.md

@@ -44,10 +44,8 @@ task_categories:
   - conditional-text-generation
   release_v3-0_en:
   - conditional-text-generation
-  - structure-prediction
   release_v3-0_ru:
   - conditional-text-generation
-  - structure-prediction
   webnlg_challenge_2017:
   - conditional-text-generation
 task_ids:
@@ -62,14 +60,13 @@ task_ids:
   release_v2_constrained:
   - other-stuctured-to-text
   release_v3-0_en:
-  - conditional-text-generation
-  - parsing
+  - other-stuctured-to-text
   release_v3-0_ru:
-  - conditional-text-generation
-  - parsing
+  - other-stuctured-to-text
   webnlg_challenge_2017:
   - other-stuctured-to-text
 paperswithcode_id: webnlg
+pretty_name: WebNLG
 ---
 
 # Dataset Card for WebNLG
@@ -124,7 +121,7 @@ aggregation (how to avoid repetitions) and surface realisation
 
 ### Supported Tasks and Leaderboards
 
-The dataset supports a `other-structured-to-text` task which requires a model takes a set of RDF (Resource Description Format) triples from a database (DBpedia) of the form (subject, property, object) as input and write out a natural language sentence expressing the information contained in the triples. The dataset has supportd two challenges: the [WebNLG2017](https://www.aclweb.org/anthology/W17-3518/) and [WebNLG2020](https://gerbil-nlg.dice-research.org/gerbil/webnlg2020results) challenge. Results were ordered by their [METEOR](https://huggingface.co/metrics/meteor) to the reference, but the leaderboards report a range of other metrics including [BLEU](https://huggingface.co/metrics/bleu), [BERTscore](https://huggingface.co/metrics/bertscore), and [BLEURT](https://huggingface.co/metrics/bleurt). The v3 release (`release_v3.0_en`, `release_v3.0_ru`) for the WebNLG2020 challenge also supports a semantic `parsing` task.
+The dataset supports a Structured to Text task which requires a model takes a set of RDF (Resource Description Format) triples from a database (DBpedia) of the form (subject, property, object) as input and write out a natural language sentence expressing the information contained in the triples. The dataset has supportd two challenges: the [WebNLG2017](https://www.aclweb.org/anthology/W17-3518/) and [WebNLG2020](https://gerbil-nlg.dice-research.org/gerbil/webnlg2020results) challenge. Results were ordered by their [METEOR](https://huggingface.co/metrics/meteor) to the reference, but the leaderboards report a range of other metrics including [BLEU](https://huggingface.co/metrics/bleu), [BERTscore](https://huggingface.co/metrics/bertscore), and [BLEURT](https://huggingface.co/metrics/bleurt). The v3 release (`release_v3.0_en`, `release_v3.0_ru`) for the WebNLG2020 challenge also supports a semantic `parsing` task.
 
 ### Languages
 

dataset_infos.json

@@ -1 +1 @@
-{"webnlg_challenge_2017": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "webnlg_challenge_2017", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5594812, "num_examples": 6940, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 706653, "num_examples": 872, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 3122533, "num_examples": 4615, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 9423998, "size_in_bytes": 34814586}, "release_v1": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "release_v1", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"full": {"name": "full", "num_bytes": 11684308, "num_examples": 14237, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 11684308, "size_in_bytes": 37074896}, "release_v2": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "release_v2", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10830413, "num_examples": 12876, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1360033, "num_examples": 1619, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1324934, "num_examples": 1600, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 13515380, "size_in_bytes": 38905968}, "release_v2_constrained": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "release_v2_constrained", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10853434, "num_examples": 12895, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1421590, "num_examples": 1594, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1243182, "num_examples": 1606, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 13518206, "size_in_bytes": 38908794}, "release_v2.1": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "release_v2.1", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10848793, "num_examples": 12876, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1362072, "num_examples": 1619, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1325860, "num_examples": 1600, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 13536725, "size_in_bytes": 38927313}, "release_v2.1_constrained": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "release_v2.1_constrained", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11040016, "num_examples": 12895, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1284044, "num_examples": 1594, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1212665, "num_examples": 1606, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 13536725, "size_in_bytes": 38927313}, "release_v3.0_en": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "release_v3.0_en", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11084860, "num_examples": 13211, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1394243, "num_examples": 1667, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 4039282, "num_examples": 5713, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 16518385, "size_in_bytes": 41908973}, "release_v3.0_ru": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "web_nlg", "config_name": "release_v3.0_ru", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 9550340, "num_examples": 5573, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1314226, "num_examples": 790, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 3656501, "num_examples": 3410, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip": {"num_bytes": 25390588, "checksum": "287290957f7352c9e3b64cdc5957faba8ed5d835f34f2106ba5666a77fdb1cfb"}}, "download_size": 25390588, "post_processing_size": null, "dataset_size": 14521067, "size_in_bytes": 39911655}}
+{"webnlg_challenge_2017": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "webnlg_challenge_2017", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5594812, "num_examples": 6940, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 706653, "num_examples": 872, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 3122533, "num_examples": 4615, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 9423998, "size_in_bytes": 34923349}, "release_v1": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "release_v1", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"full": {"name": "full", "num_bytes": 11684308, "num_examples": 14237, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 11684308, "size_in_bytes": 37183659}, "release_v2": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "release_v2", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10830413, "num_examples": 12876, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1360033, "num_examples": 1619, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1324934, "num_examples": 1600, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 13515380, "size_in_bytes": 39014731}, "release_v2_constrained": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "release_v2_constrained", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10853434, "num_examples": 12895, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1421590, "num_examples": 1594, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1243182, "num_examples": 1606, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 13518206, "size_in_bytes": 39017557}, "release_v2.1": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "release_v2.1", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10848793, "num_examples": 12876, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1362072, "num_examples": 1619, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1325860, "num_examples": 1600, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 13536725, "size_in_bytes": 39036076}, "release_v2.1_constrained": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "release_v2.1_constrained", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11040016, "num_examples": 12895, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1284044, "num_examples": 1594, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 1212665, "num_examples": 1606, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 13536725, "size_in_bytes": 39036076}, "release_v3.0_en": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "release_v3.0_en", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 11084860, "num_examples": 13211, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1394243, "num_examples": 1667, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 4039282, "num_examples": 5713, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 16518385, "size_in_bytes": 42017736}, "release_v3.0_ru": {"description": "The WebNLG challenge consists in mapping data to text. The training data consists\nof Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation\nof these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).\n\na. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)\nb. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot\n\nAs the example illustrates, the task involves specific NLG subtasks such as sentence segmentation\n(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),\naggregation (how to avoid repetitions) and surface realisation\n(how to build a syntactically correct and natural sounding text).\n", "citation": "@inproceedings{web_nlg,\n  author    = {Claire Gardent and\n               Anastasia Shimorina and\n               Shashi Narayan and\n               Laura Perez{-}Beltrachini},\n  editor    = {Regina Barzilay and\n               Min{-}Yen Kan},\n  title     = {Creating Training Corpora for {NLG} Micro-Planners},\n  booktitle = {Proceedings of the 55th Annual Meeting of the\n               Association for Computational Linguistics,\n               {ACL} 2017, Vancouver, Canada, July 30 - August 4,\n               Volume 1: Long Papers},\n  pages     = {179--188},\n  publisher = {Association for Computational Linguistics},\n  year      = {2017},\n  url       = {https://doi.org/10.18653/v1/P17-1017},\n  doi       = {10.18653/v1/P17-1017}\n}\n", "homepage": "https://webnlg-challenge.loria.fr/", "license": "", "features": {"category": {"dtype": "string", "id": null, "_type": "Value"}, "size": {"dtype": "int32", "id": null, "_type": "Value"}, "eid": {"dtype": "string", "id": null, "_type": "Value"}, "original_triple_sets": {"feature": {"otriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "modified_triple_sets": {"feature": {"mtriple_set": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}, "shape": {"dtype": "string", "id": null, "_type": "Value"}, "shape_type": {"dtype": "string", "id": null, "_type": "Value"}, "lex": {"feature": {"comment": {"dtype": "string", "id": null, "_type": "Value"}, "lid": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "test_category": {"dtype": "string", "id": null, "_type": "Value"}, "dbpedia_links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "links": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "web_nlg", "config_name": "release_v3.0_ru", "version": "0.0.0", "splits": {"train": {"name": "train", "num_bytes": 9550340, "num_examples": 5573, "dataset_name": "web_nlg"}, "dev": {"name": "dev", "num_bytes": 1314226, "num_examples": 790, "dataset_name": "web_nlg"}, "test": {"name": "test", "num_bytes": 3656501, "num_examples": 3410, "dataset_name": "web_nlg"}}, "download_checksums": {"https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip": {"num_bytes": 25499351, "checksum": "d6837063d6ef2a2e05418c1511f989c85fd9fffd21f5bd04bc5b34886f24c94e"}}, "download_size": 25499351, "post_processing_size": null, "dataset_size": 14521067, "size_in_bytes": 40020418}}

dummy/release_v1/0.0.0/dummy_data.zip

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dummy/release_v2.1/0.0.0/dummy_data.zip

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dummy/release_v2.1_constrained/0.0.0/dummy_data.zip

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web_nlg.py

@@ -60,7 +60,7 @@ aggregation (how to avoid repetitions) and surface realisation
 (how to build a syntactically correct and natural sounding text).
 """
 
-_URL = "https://gitlab.com/shimorina/webnlg-dataset/-/archive/master/webnlg-dataset-master.zip"
+_URL = "https://gitlab.com/shimorina/webnlg-dataset/-/archive/587fa698bec705efbefe72a235a6019c2b9b8b6c/webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c.zip"
 
 _FILE_PATHS = {
     "webnlg_challenge_2017": {
@@ -239,7 +239,8 @@ class WebNlg(datasets.GeneratorBasedBuilder):
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "filedirs": [
-                        os.path.join(data_dir, "webnlg-dataset-master", dir_suf) for dir_suf in dir_suffix_list
+                        os.path.join(data_dir, "webnlg-dataset-587fa698bec705efbefe72a235a6019c2b9b8b6c", dir_suf)
+                        for dir_suf in dir_suffix_list
                     ],
                 },
             )