Sebastian Gehrmann commited on
Commit
4cb7466
1 Parent(s): 32beafc
Files changed (1) hide show
  1. cochrane-simplification.json +15 -11
cochrane-simplification.json CHANGED
@@ -6,10 +6,10 @@
6
  "leaderboard-description": "N/A",
7
  "contact-name": "Ashwin Devaraj",
8
  "contact-email": "ashwin.devaraj@utexas.edu",
9
- "data-url": "https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts",
10
- "paper-url": "https://aclanthology.org/2021.naacl-main.395/",
11
- "paper-bibtext": "@inproceedings{devaraj-etal-2021-paragraph,\n title = \"Paragraph-level Simplification of Medical Texts\",\n author = \"Devaraj, Ashwin and\n Marshall, Iain and\n Wallace, Byron and\n Li, Junyi Jessy\",\n booktitle = \"Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies\",\n month = jun,\n year = \"2021\",\n address = \"Online\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://aclanthology.org/2021.naacl-main.395\",\n doi = \"10.18653/v1/2021.naacl-main.395\",\n pages = \"4972--4984\",\n}",
12
- "website": "https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts"
13
  },
14
  "languages": {
15
  "is-multilingual": "no",
@@ -33,9 +33,12 @@
33
  "gem-added-by": "Ashwin Devaraj (The University of Texas at Austin)"
34
  },
35
  "structure": {
36
- "data-fields": "gem_id: string, a unique identifier for the example\ndoi: string, DOI identifier for the Cochrane review from which the example was generated\nsource: string, an excerpt from an abstract of a Cochrane review\ntarget: string, an excerpt from the plain-language summary of a Cochrane review that roughly aligns with the source text",
37
- "structure-example": "{\n \"gem_id\": \"gem-cochrane-simplification-train-766\",\n \"doi\": \"10.1002/14651858.CD002173.pub2\",\n \"source\": \"Of 3500 titles retrieved from the literature, 24 papers reporting on 23 studies could be included in the review. The studies were published between 1970 and 1997 and together included 1026 participants. Most were cross-over studies. Few studies provided sufficient information to judge the concealment of allocation. Four studies provided results for the percentage of symptom-free days. Pooling the results did not reveal a statistically significant difference between sodium cromoglycate and placebo. For the other pooled outcomes, most of the symptom-related outcomes and bronchodilator use showed statistically significant results, but treatment effects were small. Considering the confidence intervals of the outcome measures, a clinically relevant effect of sodium cromoglycate cannot be excluded. The funnel plot showed an under-representation of small studies with negative results, suggesting publication bias. There is insufficient evidence to be sure about the efficacy of sodium cromoglycate over placebo. Publication bias is likely to have overestimated the beneficial effects of sodium cromoglycate as maintenance therapy in childhood asthma.\",\n \"target\": \"In this review we aimed to determine whether there is evidence for the effectiveness of inhaled sodium cromoglycate as maintenance treatment in children with chronic asthma. Most of the studies were carried out in small groups of patients. Furthermore, we suspect that not all studies undertaken have been published. The results show that there is insufficient evidence to be sure about the beneficial effect of sodium cromoglycate compared to placebo. However, for several outcome measures the results favoured sodium cromoglycate.\"\n}",
38
- "structure-splits": "train: 3568 examples\nvalidation: 411 examples\ntest: 480 examples"
 
 
 
39
  }
40
  },
41
  "curation": {
@@ -92,7 +95,7 @@
92
  "distinction-description": "N/A",
93
  "contribution": "This dataset is the first paragraph-level simplification dataset published (as prior work had primarily focused on simplifying individual sentences). Furthermore, this dataset is in the medical domain, which is an especially useful domain for text simplification.",
94
  "model-ability": "This dataset measures the ability for a model to simplify paragraphs of medical text through the omission non-salient information and simplification of medical jargon.",
95
- "sole-language-task-dataset": "no"
96
  },
97
  "curation": {
98
  "has-additional-curation": "no",
@@ -106,15 +109,16 @@
106
  },
107
  "results": {
108
  "results": {
109
- "other-metrics-definitions": "SARI\nBLEU",
110
  "has-previous-results": "yes",
111
  "current-evaluation": "N/A",
112
  "previous-results": "The paper which introduced this dataset trained BART models (pretrained on XSum) with unlikelihood training to produce simplification models achieving maximum SARI and BLEU scores of 40 and 43 respectively.",
113
  "model-abilities": "This dataset measures the ability for a model to simplify paragraphs of medical text through the omission non-salient information and simplification of medical jargon.",
114
  "metrics": [
115
- "Other: Other Metrics"
 
116
  ],
117
- "original-evaluation": "SARI - measures quality of text simplification\nBLEU - precision-based method to used to score quality of machine translation"
118
  }
119
  },
120
  "considerations": {
 
6
  "leaderboard-description": "N/A",
7
  "contact-name": "Ashwin Devaraj",
8
  "contact-email": "ashwin.devaraj@utexas.edu",
9
+ "data-url": "[Link](https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts)",
10
+ "paper-url": "[Link](https://aclanthology.org/2021.naacl-main.395/)",
11
+ "paper-bibtext": "```\n@inproceedings{devaraj-etal-2021-paragraph,\n title = \"Paragraph-level Simplification of Medical Texts\",\n author = \"Devaraj, Ashwin and\n Marshall, Iain and\n Wallace, Byron and\n Li, Junyi Jessy\",\n booktitle = \"Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies\",\n month = jun,\n year = \"2021\",\n address = \"Online\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://aclanthology.org/2021.naacl-main.395\",\n doi = \"10.18653/v1/2021.naacl-main.395\",\n pages = \"4972--4984\",\n}\n```",
12
+ "website": "[Link](https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts)"
13
  },
14
  "languages": {
15
  "is-multilingual": "no",
 
33
  "gem-added-by": "Ashwin Devaraj (The University of Texas at Austin)"
34
  },
35
  "structure": {
36
+ "data-fields": "- `gem_id`: string, a unique identifier for the example\n- `doi`: string, DOI identifier for the Cochrane review from which the example was generated\n- `source`: string, an excerpt from an abstract of a Cochrane review\n- `target`: string, an excerpt from the plain-language summary of a Cochrane review that roughly aligns with the source text",
37
+ "structure-example": "```\n{\n \"gem_id\": \"gem-cochrane-simplification-train-766\",\n \"doi\": \"10.1002/14651858.CD002173.pub2\",\n \"source\": \"Of 3500 titles retrieved from the literature, 24 papers reporting on 23 studies could be included in the review. The studies were published between 1970 and 1997 and together included 1026 participants. Most were cross-over studies. Few studies provided sufficient information to judge the concealment of allocation. Four studies provided results for the percentage of symptom-free days. Pooling the results did not reveal a statistically significant difference between sodium cromoglycate and placebo. For the other pooled outcomes, most of the symptom-related outcomes and bronchodilator use showed statistically significant results, but treatment effects were small. Considering the confidence intervals of the outcome measures, a clinically relevant effect of sodium cromoglycate cannot be excluded. The funnel plot showed an under-representation of small studies with negative results, suggesting publication bias. There is insufficient evidence to be sure about the efficacy of sodium cromoglycate over placebo. Publication bias is likely to have overestimated the beneficial effects of sodium cromoglycate as maintenance therapy in childhood asthma.\",\n \"target\": \"In this review we aimed to determine whether there is evidence for the effectiveness of inhaled sodium cromoglycate as maintenance treatment in children with chronic asthma. Most of the studies were carried out in small groups of patients. Furthermore, we suspect that not all studies undertaken have been published. The results show that there is insufficient evidence to be sure about the beneficial effect of sodium cromoglycate compared to placebo. However, for several outcome measures the results favoured sodium cromoglycate.\"\n}\n```",
38
+ "structure-splits": "- `train`: 3568 examples\n- `validation`: 411 examples\n- `test`: 480 examples"
39
+ },
40
+ "what": {
41
+ "dataset": "Cochrane is an English dataset for paragraph-level simplification of medical texts. Cochrane is a database of systematic reviews of clinical questions, many of which have summaries in plain English targeting readers without a university education. The dataset comprises about 4,500 of such pairs. "
42
  }
43
  },
44
  "curation": {
 
95
  "distinction-description": "N/A",
96
  "contribution": "This dataset is the first paragraph-level simplification dataset published (as prior work had primarily focused on simplifying individual sentences). Furthermore, this dataset is in the medical domain, which is an especially useful domain for text simplification.",
97
  "model-ability": "This dataset measures the ability for a model to simplify paragraphs of medical text through the omission non-salient information and simplification of medical jargon.",
98
+ "sole-language-task-dataset": "N/A"
99
  },
100
  "curation": {
101
  "has-additional-curation": "no",
 
109
  },
110
  "results": {
111
  "results": {
112
+ "other-metrics-definitions": "SARI measures the quality of text simplification\n",
113
  "has-previous-results": "yes",
114
  "current-evaluation": "N/A",
115
  "previous-results": "The paper which introduced this dataset trained BART models (pretrained on XSum) with unlikelihood training to produce simplification models achieving maximum SARI and BLEU scores of 40 and 43 respectively.",
116
  "model-abilities": "This dataset measures the ability for a model to simplify paragraphs of medical text through the omission non-salient information and simplification of medical jargon.",
117
  "metrics": [
118
+ "Other: Other Metrics",
119
+ "BLEU"
120
  ],
121
+ "original-evaluation": ""
122
  }
123
  },
124
  "considerations": {