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Sebastian Gehrmann commited on
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Data Card.

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  1. README.md +37 -21
  2. wiki_cat_sum.json +11 -7
README.md CHANGED
@@ -36,7 +36,7 @@ You can find the main data card on the [GEM Website](https://gem-benchmark.com/d
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  ### Dataset Summary
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- Placeholder
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  You can load the dataset via:
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  ```
@@ -46,10 +46,10 @@ data = datasets.load_dataset('GEM/wiki_cat_sum')
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  The data loader can be found [here](https://huggingface.co/datasets/GEM/wiki_cat_sum).
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  #### website
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- https://github.com/lauhaide/WikiCatSum
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  #### paper
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- https://arxiv.org/abs/1906.04687
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  #### authors
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  Laura Perez-Beltrachini, Yang Liu, Mirella Lapata (University of Edinburgh) Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, Noam Shazeer (GoogleBrain)
@@ -62,24 +62,25 @@ Laura Perez-Beltrachini, Yang Liu, Mirella Lapata (University of Edinburgh) Pete
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  <!-- info: What is the webpage for the dataset (if it exists)? -->
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  <!-- scope: telescope -->
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- https://github.com/lauhaide/WikiCatSum
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  #### Download
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  <!-- info: What is the link to where the original dataset is hosted? -->
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  <!-- scope: telescope -->
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- https://datashare.ed.ac.uk/handle/10283/3368
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  #### Paper
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  <!-- info: What is the link to the paper describing the dataset (open access preferred)? -->
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  <!-- scope: telescope -->
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- https://arxiv.org/abs/1906.04687
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  #### BibTex
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  <!-- info: Provide the BibTex-formatted reference for the dataset. Please use the correct published version (ACL anthology, etc.) instead of google scholar created Bibtex. -->
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  <!-- scope: microscope -->
 
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  @inproceedings{perez-beltrachini-etal-2019-generating,
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  title = "Generating Summaries with Topic Templates and Structured Convolutional Decoders",
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  author = "Perez-Beltrachini, Laura and
@@ -93,6 +94,7 @@ https://arxiv.org/abs/1906.04687
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  url = "https://aclanthology.org/P19-1504",
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  doi = "10.18653/v1/P19-1504",
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  }
 
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  #### Contact Name
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@@ -196,10 +198,31 @@ Ronald Cardenas (University of Edinburgh) Laura Perez-Beltrachini (University of
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  <!-- info: List and describe the fields present in the dataset. -->
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  <!-- scope: telescope -->
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- id: ID of the data example
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- title: Is the Wikipedia article's title
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- paragraphs: Is the ranked list of paragraphs from the set of crawled texts
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- summary: Is constituted by a list of sentences together with their corresponding topic label
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  #### Data Splits
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@@ -211,7 +234,7 @@ Nb of instances in train/valid/test are 50,938/2,855/2,831
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  <!-- info: Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g., if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here. -->
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  <!-- scope: microscope -->
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- iid
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@@ -278,21 +301,14 @@ no
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  <!-- info: Getting started with in-depth research on the task. Add relevant pointers to resources that researchers can consult when they want to get started digging deeper into the task. -->
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  <!-- scope: microscope -->
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- Generating Wikipedia by Summarizing Long Sequences
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- https://arxiv.org/abs/1801.10198
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-
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- Generating Summaries with Topic Templates and Structured Convolutional Decoders
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- https://arxiv.org/abs/1906.04687
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-
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- Noisy Self-Knowledge Distillation for Text Summarization
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- https://arxiv.org/abs/2009.07032
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  And all references in these papers.
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-
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-
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  ## Previous Results
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  ### Previous Results
 
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  ### Dataset Summary
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+ 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.
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  You can load the dataset via:
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  ```
 
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  The data loader can be found [here](https://huggingface.co/datasets/GEM/wiki_cat_sum).
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  #### website
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+ [Github](https://github.com/lauhaide/WikiCatSum)
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  #### paper
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+ [Arxiv](https://arxiv.org/abs/1906.04687)
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  #### authors
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  Laura Perez-Beltrachini, Yang Liu, Mirella Lapata (University of Edinburgh) Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, Noam Shazeer (GoogleBrain)
 
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63
  <!-- info: What is the webpage for the dataset (if it exists)? -->
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  <!-- scope: telescope -->
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+ [Github](https://github.com/lauhaide/WikiCatSum)
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  #### Download
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69
  <!-- info: What is the link to where the original dataset is hosted? -->
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  <!-- scope: telescope -->
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+ [Website](https://datashare.ed.ac.uk/handle/10283/3368)
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  #### Paper
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  <!-- info: What is the link to the paper describing the dataset (open access preferred)? -->
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  <!-- scope: telescope -->
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+ [Arxiv](https://arxiv.org/abs/1906.04687)
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  #### BibTex
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  <!-- info: Provide the BibTex-formatted reference for the dataset. Please use the correct published version (ACL anthology, etc.) instead of google scholar created Bibtex. -->
82
  <!-- scope: microscope -->
83
+ ```
84
  @inproceedings{perez-beltrachini-etal-2019-generating,
85
  title = "Generating Summaries with Topic Templates and Structured Convolutional Decoders",
86
  author = "Perez-Beltrachini, Laura and
 
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  url = "https://aclanthology.org/P19-1504",
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  doi = "10.18653/v1/P19-1504",
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  }
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+ ```
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  #### Contact Name
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  <!-- info: List and describe the fields present in the dataset. -->
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  <!-- scope: telescope -->
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+ - `id`: ID of the data example
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+ - `title`: Is the Wikipedia article's title
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+ - `paragraphs`: Is the ranked list of paragraphs from the set of crawled texts
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+ - `summary`: Is constituted by a list of sentences together with their corresponding topic label
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+
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+ #### Example Instance
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+
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+ <!-- info: Provide a JSON formatted example of a typical instance in the dataset. -->
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+ <!-- scope: periscope -->
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+ This is a truncated example from the animal setting:
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+
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+ ```
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+ {'gem_id': 'animal-train-1',
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+ 'gem_parent_id': 'animal-train-1',
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+ 'id': '2652',
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+ 'paragraphs': ["lytrosis (hulst) of louisiana vernon antoine brou jr. 2005. southern lepidopterists' news, 27: 7 ., ..."],
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+ '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.'],
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+ 'summary': {'text': ['lytrosis unitaria , the common lytrosis moth , is a species of moth of the geometridae family .',
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+ '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 .',
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+ 'the wingspan is about 50 mm .',
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+ 'the larvae feed on rosa , crataegus , amelanchier , acer , quercus and viburnum species . '],
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+ 'topic': [29, 20, 9, 8]},
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+ '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.',
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+ 'title': 'lytrosis unitaria'}
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+ ```
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  #### Data Splits
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  <!-- info: Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g., if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here. -->
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  <!-- scope: microscope -->
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+ The data was split i.i.d., i.e. uniformly split into training, validation, and test datasets.
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  <!-- info: Getting started with in-depth research on the task. Add relevant pointers to resources that researchers can consult when they want to get started digging deeper into the task. -->
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  <!-- scope: microscope -->
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+ - [Generating Wikipedia by Summarizing Long Sequences](https://arxiv.org/abs/1801.10198)
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+ - [Generating Summaries with Topic Templates and Structured Convolutional Decoders](https://arxiv.org/abs/1906.04687)
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+ - [Noisy Self-Knowledge Distillation for Text Summarization](https://arxiv.org/abs/2009.07032)
 
 
 
 
 
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  And all references in these papers.
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  ## Previous Results
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  ### Previous Results
wiki_cat_sum.json CHANGED
@@ -74,7 +74,7 @@
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  "additional-splits-capacicites": "N/A"
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  },
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  "starting": {
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- "research-pointers": "Generating Wikipedia by Summarizing Long Sequences\nhttps://arxiv.org/abs/1801.10198\n\nGenerating Summaries with Topic Templates and Structured Convolutional Decoders\nhttps://arxiv.org/abs/1906.04687\n\nNoisy Self-Knowledge Distillation for Text Summarization\nhttps://arxiv.org/abs/2009.07032\n\nAnd all references in these papers.\n\n"
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  }
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  },
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  "results": {
@@ -127,10 +127,10 @@
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  "has-leaderboard": "no",
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  "leaderboard-url": "N/A",
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  "leaderboard-description": "N/A",
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- "website": "https://github.com/lauhaide/WikiCatSum",
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- "data-url": "https://datashare.ed.ac.uk/handle/10283/3368",
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- "paper-url": "https://arxiv.org/abs/1906.04687",
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- "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}",
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  "contact-name": "Laura Perez-Beltrachini",
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  "contact-email": "lperez@ed.ac.uk"
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  },
@@ -157,9 +157,13 @@
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  "gem-added-by": "Ronald Cardenas (University of Edinburgh) Laura Perez-Beltrachini (University of Edinburgh) "
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  },
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  "structure": {
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- "data-fields": "id: ID of the data example \ntitle: Is the Wikipedia article's title\nparagraphs: Is the ranked list of paragraphs from the set of crawled texts\nsummary: Is constituted by a list of sentences together with their corresponding topic label",
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  "structure-splits": "Nb of instances in train/valid/test are 50,938/2,855/2,831",
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- "structure-splits-criteria": "iid"
 
 
 
 
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  }
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  }
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  }
 
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  "additional-splits-capacicites": "N/A"
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  },
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  "starting": {
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+ "research-pointers": "- [Generating Wikipedia by Summarizing Long Sequences](https://arxiv.org/abs/1801.10198)\n- [Generating Summaries with Topic Templates and Structured Convolutional Decoders](https://arxiv.org/abs/1906.04687)\n- [Noisy Self-Knowledge Distillation for Text Summarization](https://arxiv.org/abs/2009.07032)\n\nAnd all references in these papers."
78
  }
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  },
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  "results": {
 
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  "has-leaderboard": "no",
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  "leaderboard-url": "N/A",
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  "leaderboard-description": "N/A",
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+ "website": "[Github](https://github.com/lauhaide/WikiCatSum)",
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+ "data-url": "[Website](https://datashare.ed.ac.uk/handle/10283/3368)",
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+ "paper-url": "[Arxiv](https://arxiv.org/abs/1906.04687)",
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+ "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```",
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  "contact-name": "Laura Perez-Beltrachini",
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  "contact-email": "lperez@ed.ac.uk"
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  },
 
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  "gem-added-by": "Ronald Cardenas (University of Edinburgh) Laura Perez-Beltrachini (University of Edinburgh) "
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  },
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  "structure": {
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+ "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",
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  "structure-splits": "Nb of instances in train/valid/test are 50,938/2,855/2,831",
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+ "structure-splits-criteria": "The data was split i.i.d., i.e. uniformly split into training, validation, and test datasets.",
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+ "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```"
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+ },
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+ "what": {
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+ "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."
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  }
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  }
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  }