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README.md CHANGED
@@ -6,8 +6,56 @@ task_categories:
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  - text-generation
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  - text2text-generation
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  language:
 
 
 
 
 
 
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  - en
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  pretty_name: MegaWika-Report-Generation
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  ---
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  # Dataset Card for MegaWika for Report Generation
@@ -35,19 +83,72 @@ See the original [HuggingFace](https://huggingface.co/datasets/hltcoe/megawika)
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  ### Languages
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- MegaWika is divided by Wikipedia language. There are 50 languages, including English, each designated by their 2-character ISO language code. Currently only a few languages are available, but more are coming!
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Dataset Structure
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- The dataset is divided into two main sections, "mono" for monolingual report generation and "cross-lingual" for cross-lingual report generation.
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- t is further subdivided into two options, (1) generating the entire Wikipedia sections from multiple citations ("all") or (2) generating segments of each section in an iterative fashion ("iterative").
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- Then the dataset is divided by language pairs.
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  ### Data Instances
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  Given the rest of the fields (except for the ID) the goals is to produce the `gold_section_text` (e.g. given the title, intro, section name, and citations).
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- `num_docs` is provided for filtering on the number of docs for the multi-doc summarization. Note that in the iterative setting is it just one citation.
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  ### Data Fields
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@@ -62,6 +163,7 @@ The detailed structure of an instance is as follows:
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  "previous_text": <string : used for the iterative task format, the previous text in the section already to condition on>
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  "question": <string : a natural language question that could be used for query-focused summarization, generated by ChatGPT>
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  "gold_section_text": <string : the text of the original Wikipedia section, e.g. the gold label for summarization>
 
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  "citations": <list of strings : the text of the citations (e.g. reference) for the section/chunk >
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  }
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  ```
@@ -85,7 +187,18 @@ And contact the authors.
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  *Take down*: We will comply to legitimate requests by removing the affected sources from the next release of the dataset.
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- ## Additional Information
 
 
 
 
 
 
 
 
 
 
 
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  ### Dataset Curators
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  - text-generation
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  - text2text-generation
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  language:
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+ - af
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+ - ar
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+ - az
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+ - bn
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+ - cs
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+ - de
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  - en
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+ - es
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+ - et
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+ - fa
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+ - fi
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+ - fr
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+ - ga
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+ - gl
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+ - gu
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+ - he
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+ - hi
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+ - hr
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+ - id
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+ - it
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+ - ja
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+ - ka
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+ - kk
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+ - km
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+ - ko
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+ - lt
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+ - lv
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+ - mk
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+ - ml
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+ - mn
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+ - mr
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+ - my
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+ - ne
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+ - nl
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+ - pl
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+ - ps
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+ - pt
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+ - ro
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+ - ru
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+ - si
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+ - sl
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+ - sv
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+ - ta
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+ - th
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+ - tr
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+ - uk
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+ - ur
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+ - vi
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+ - xh
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+ - zh
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  pretty_name: MegaWika-Report-Generation
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  ---
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  # Dataset Card for MegaWika for Report Generation
 
83
 
84
  ### Languages
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+ MegaWika is divided by Wikipedia language. There are 50 languages, including English, each designated by their 2-character ISO language code.
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+
88
+ ### Languages
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+
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+ MegaWika is divided by Wikipedia language. There are 50 languages, including English, each designated by their 2-character ISO language code:
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+ - `af`: Afrikaans
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+ - `ar`: Arabic
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+ - `az`: Azeri (Azerbaijani)
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+ - `bn`: Bengali
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+ - `cs`: Czech
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+ - `de`: German (Deutsch)
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+ - `en`: English
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+ - `es`: Spanish (Español)
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+ - `et`: Estonian
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+ - `fa`: Farsi (Persian)
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+ - `fi`: Finnish
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+ - `fr`: French
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+ - `ga`: Irish (Gaelic)
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+ - `gl`: Galician
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+ - `gu`: Gujarati
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+ - `he`: Hebrew
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+ - `hi`: Hindi
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+ - `hr`: Hungarian
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+ - `id`: Indonesian
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+ - `it`: Italian
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+ - `ja`: Japanese
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+ - `ka`: Georgian (Kartvelian/Kartlian)
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+ - `kk`: Kazakh
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+ - `km`: Khmer
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+ - `ko`: Korean
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+ - `lt`: Lithuanian
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+ - `lv`: Latvian
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+ - `mk`: Macedonian (Makedonski)
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+ - `ml`: Malay (Malayalam)
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+ - `mn`: Mongolian
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+ - `mr`: Marathi
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+ - `my`: Burmese (Myanmar language)
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+ - `ne`: Nepali
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+ - `nl`: Dutch (Nederlands)
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+ - `pl`: Polish
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+ - `ps`: Pashto
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+ - `pt`: Portuguese
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+ - `ro`: Romanian
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+ - `ru`: Russian
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+ - `si`: Sinhalese (Sri Lankan language)
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+ - `sl`: Slovenian
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+ - `sv`: Swedish (Svenska)
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+ - `ta`: Tamil
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+ - `th`: Thai
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+ - `tr`: Turkish
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+ - `uk`: Ukrainian
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+ - `ur`: Urdu
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+ - `vi`: Vietnamese
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+ - `xh`: Xhosa
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+ - `zh`: Chinese (Zhōng wén)
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142
 
143
  ## Dataset Structure
144
 
145
+ The dataset is divided into two main sections (1) generating the entire Wikipedia sections from multiple citations ("all") or (2) generating segments of each section in an iterative fashion ("iterative").
146
+ Then the dataset is divided by language pairs. Note that each language can be used cross-lingually by using the `en_gold_section_text` key.
 
147
 
148
  ### Data Instances
149
 
150
  Given the rest of the fields (except for the ID) the goals is to produce the `gold_section_text` (e.g. given the title, intro, section name, and citations).
151
+ `num_docs` is provided for filtering on the number of docs for the multi-doc summarization. Note that in the iterative setting is it just one citation. **NOTE: `num_docs` is incorrect for now, will be updated.**
152
 
153
  ### Data Fields
154
 
 
163
  "previous_text": <string : used for the iterative task format, the previous text in the section already to condition on>
164
  "question": <string : a natural language question that could be used for query-focused summarization, generated by ChatGPT>
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  "gold_section_text": <string : the text of the original Wikipedia section, e.g. the gold label for summarization>
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+ "en_gold_section_text": <string : the English version of the text from the original Wikipedia section, e.g. the gold label for cross-lingual summarization>
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  "citations": <list of strings : the text of the citations (e.g. reference) for the section/chunk >
168
  }
169
  ```
 
187
 
188
  *Take down*: We will comply to legitimate requests by removing the affected sources from the next release of the dataset.
189
 
190
+ ## Usage
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+
192
+ ```
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+ # all of the dataset (not recommended)
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+ dataset = load_dataset("hltcoe/megawika-report-generation")
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+
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+ # just the `all`` section data (all splits)
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+ dataset = load_dataset("hltcoe/megawika-report-generation", data_dir="all")
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+
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+ # just the `all` English test set (can replace with "validation" or "train", or other langs)
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+ dataset = load_dataset("hltcoe/megawika-report-generation", data_dir="all/en", split="test")
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+ ```
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  ### Dataset Curators
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