Datasets:
Sebastian Gehrmann
commited on
Commit
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a76c6c3
1
Parent(s):
5648408
- dataset_infos.json +1 -1
- wiki_cat_sum.json +10 -6
- wiki_cat_sum.py +13 -10
dataset_infos.json
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|
wiki_cat_sum.json
CHANGED
@@ -127,10 +127,10 @@
|
|
127 |
"has-leaderboard": "no",
|
128 |
"leaderboard-url": "N/A",
|
129 |
"leaderboard-description": "N/A",
|
130 |
-
"website": "https://github.com/lauhaide/WikiCatSum",
|
131 |
-
"data-url": "https://datashare.ed.ac.uk/handle/10283/3368",
|
132 |
-
"paper-url": "https://arxiv.org/abs/1906.04687",
|
133 |
-
"paper-bibtext": "@inproceedings{perez-beltrachini-etal-2019-generating,\n title = \"Generating Summaries with Topic Templates and Structured Convolutional Decoders\",\n author = \"Perez-Beltrachini, Laura and\n Liu, Yang and\n Lapata, Mirella\",\n booktitle = \"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics\",\n month = jul,\n year = \"2019\",\n address = \"Florence, Italy\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://aclanthology.org/P19-1504\",\n doi = \"10.18653/v1/P19-1504\",\n}",
|
134 |
"contact-name": "Laura Perez-Beltrachini",
|
135 |
"contact-email": "[email protected]"
|
136 |
},
|
@@ -157,9 +157,13 @@
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|
157 |
"gem-added-by": "Ronald Cardenas (University of Edinburgh) Laura Perez-Beltrachini (University of Edinburgh) "
|
158 |
},
|
159 |
"structure": {
|
160 |
-
"data-fields": "id
|
161 |
"structure-splits": "Nb of instances in train/valid/test are 50,938/2,855/2,831",
|
162 |
-
"structure-splits-criteria": "
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|
|
|
|
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}
|
164 |
}
|
165 |
}
|
|
|
127 |
"has-leaderboard": "no",
|
128 |
"leaderboard-url": "N/A",
|
129 |
"leaderboard-description": "N/A",
|
130 |
+
"website": "[Github](https://github.com/lauhaide/WikiCatSum)",
|
131 |
+
"data-url": "[Website](https://datashare.ed.ac.uk/handle/10283/3368)",
|
132 |
+
"paper-url": "[Arxiv](https://arxiv.org/abs/1906.04687)",
|
133 |
+
"paper-bibtext": "```\n@inproceedings{perez-beltrachini-etal-2019-generating,\n title = \"Generating Summaries with Topic Templates and Structured Convolutional Decoders\",\n author = \"Perez-Beltrachini, Laura and\n Liu, Yang and\n Lapata, Mirella\",\n booktitle = \"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics\",\n month = jul,\n year = \"2019\",\n address = \"Florence, Italy\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://aclanthology.org/P19-1504\",\n doi = \"10.18653/v1/P19-1504\",\n}\n```",
|
134 |
"contact-name": "Laura Perez-Beltrachini",
|
135 |
"contact-email": "[email protected]"
|
136 |
},
|
|
|
157 |
"gem-added-by": "Ronald Cardenas (University of Edinburgh) Laura Perez-Beltrachini (University of Edinburgh) "
|
158 |
},
|
159 |
"structure": {
|
160 |
+
"data-fields": "- `id`: ID of the data example \n- `title`: Is the Wikipedia article's title\n- `paragraphs`: Is the ranked list of paragraphs from the set of crawled texts\n- `summary`: Is constituted by a list of sentences together with their corresponding topic label",
|
161 |
"structure-splits": "Nb of instances in train/valid/test are 50,938/2,855/2,831",
|
162 |
+
"structure-splits-criteria": "The data was split i.i.d., i.e. uniformly split into training, validation, and test datasets. ",
|
163 |
+
"structure-example": "This is a truncated example from the animal setting: \n\n```\n{'gem_id': 'animal-train-1',\n 'gem_parent_id': 'animal-train-1',\n 'id': '2652',\n 'paragraphs': [\"lytrosis (hulst) of louisiana vernon antoine brou jr. 2005. southern lepidopterists' news, 27: 7 ., ...\"],\n 'references': ['lytrosis unitaria , the common lytrosis moth, is a species of moth of the geometridae family. it is found in north america, including arkansas, georgia, iowa , massachusetts, and wisconsin. the wingspan is about 50 mm. the larvae feed on rosa, crataegus, amelanchier, acer, quercus and viburnum species.'],\n 'summary': {'text': ['lytrosis unitaria , the common lytrosis moth , is a species of moth of the geometridae family .',\n 'it is found in north america , including arkansas , georgia , iowa , massachusetts , new hampshire , new jersey , new york , north carolina , ohio , oklahoma , ontario , pennsylvania , south carolina , tennessee , texas , virginia , west virginia and wisconsin .',\n 'the wingspan is about 50 mm .',\n 'the larvae feed on rosa , crataegus , amelanchier , acer , quercus and viburnum species . '],\n 'topic': [29, 20, 9, 8]},\n 'target': 'lytrosis unitaria , the common lytrosis moth, is a species of moth of the geometridae family. it is found in north america, including arkansas, georgia, iowa , massachusetts, and wisconsin. the wingspan is about 50 mm. the larvae feed on rosa, crataegus, amelanchier, acer, quercus and viburnum species.',\n 'title': 'lytrosis unitaria'}\n```"
|
164 |
+
},
|
165 |
+
"what": {
|
166 |
+
"dataset": "WikiCatSum is an English summarization dataset in three domains: animals, companies, and film. It provides multiple paragraphs of text paired with a summary of the paragraphs."
|
167 |
}
|
168 |
}
|
169 |
}
|
wiki_cat_sum.py
CHANGED
@@ -141,7 +141,7 @@ def detokenize(text):
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|
141 |
|
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|
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class WikiCatSum(datasets.GeneratorBasedBuilder):
|
144 |
-
"""
|
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|
146 |
VERSION = datasets.Version("0.1.0")
|
147 |
|
@@ -269,15 +269,18 @@ class WikiCatSum(datasets.GeneratorBasedBuilder):
|
|
269 |
|
270 |
# If summary is a list itself, we have multi-ref.
|
271 |
if isinstance(data["summary"], list):
|
272 |
-
detok_targets = [
|
273 |
-
detokenize(
|
274 |
-
]
|
275 |
-
|
276 |
-
data["
|
277 |
-
|
278 |
-
|
279 |
-
|
280 |
-
|
|
|
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|
|
|
281 |
# elif isinstance(data["summary"]["text"], str):
|
282 |
# detok_target = detokenize(data["summary"]["text"])
|
283 |
else:
|
|
|
141 |
|
142 |
|
143 |
class WikiCatSum(datasets.GeneratorBasedBuilder):
|
144 |
+
"""A summarization dataset with multiple domains."""
|
145 |
|
146 |
VERSION = datasets.Version("0.1.0")
|
147 |
|
|
|
269 |
|
270 |
# If summary is a list itself, we have multi-ref.
|
271 |
if isinstance(data["summary"], list):
|
272 |
+
detok_targets = " ".join([
|
273 |
+
detokenize(s["text"]) for s in data["summary"]
|
274 |
+
])
|
275 |
+
|
276 |
+
data["target"] = detok_targets
|
277 |
+
data["references"] = [detok_targets]
|
278 |
+
# elif isinstance(data["summary"]["text"], list):
|
279 |
+
# detok_target = detokenize(" ".join(data["summary"]["text"]))
|
280 |
+
# print("\n\n\n\n", detok_target)
|
281 |
+
# exit()
|
282 |
+
# data["target"] = detok_target
|
283 |
+
# data["references"] = [detok_target]
|
284 |
# elif isinstance(data["summary"]["text"], str):
|
285 |
# detok_target = detokenize(data["summary"]["text"])
|
286 |
else:
|