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- README.md +120 -7
- {mono/iterative/en → all/af}/test.jsonl +2 -2
- {mono/iterative/en → all/af}/train.jsonl +2 -2
- {mono/iterative/en → all/af}/validation.jsonl +2 -2
- all/ar/test.jsonl +3 -0
- {mono/all/en → all/ar}/train.jsonl +2 -2
- {mono/all/en → all/ar}/validation.jsonl +2 -2
- all/az/test.jsonl +3 -0
- all/az/train.jsonl +3 -0
- all/az/validation.jsonl +3 -0
- all/bn/test.jsonl +3 -0
- all/bn/train.jsonl +3 -0
- all/bn/validation.jsonl +3 -0
- all/cs/test.jsonl +3 -0
- all/cs/train.jsonl +3 -0
- all/cs/validation.jsonl +3 -0
- all/de/test.jsonl +3 -0
- all/de/train.jsonl +3 -0
- all/de/validation.jsonl +3 -0
- {mono/all/en → all/en-real}/test.jsonl +2 -2
- all/en-real/train.jsonl +3 -0
- all/en-real/validation.jsonl +3 -0
- all/en/test.jsonl +3 -0
- all/en/train.jsonl +3 -0
- all/en/validation.jsonl +3 -0
- all/es/test.jsonl +3 -0
- all/es/train.jsonl +3 -0
- all/es/validation.jsonl +3 -0
- all/et/test.jsonl +3 -0
- all/et/train.jsonl +3 -0
- all/et/validation.jsonl +3 -0
- all/fa/test.jsonl +3 -0
- all/fa/train.jsonl +3 -0
- all/fa/validation.jsonl +3 -0
- all/fi/test.jsonl +3 -0
- all/fi/train.jsonl +3 -0
- all/fi/validation.jsonl +3 -0
- all/fr/test.jsonl +3 -0
- all/fr/train.jsonl +3 -0
- all/fr/validation.jsonl +3 -0
- all/ga/test.jsonl +3 -0
- all/ga/train.jsonl +3 -0
- all/ga/validation.jsonl +3 -0
- all/gl/test.jsonl +3 -0
- all/gl/train.jsonl +3 -0
- all/gl/validation.jsonl +3 -0
- all/gu/test.jsonl +3 -0
- all/gu/train.jsonl +3 -0
- all/gu/validation.jsonl +3 -0
- all/hi/test.jsonl +3 -0
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
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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.
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## Dataset Structure
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The dataset is divided into two main sections
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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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"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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```
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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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##
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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
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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.
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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:
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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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## Dataset Structure
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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").
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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.
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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. **NOTE: `num_docs` is incorrect for now, will be updated.**
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### Data Fields
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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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"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 >
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}
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```
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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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## Usage
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```
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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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# 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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# 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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{mono/iterative/en → all/af}/test.jsonl
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{mono/iterative/en → all/af}/train.jsonl
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{mono/iterative/en → all/af}/validation.jsonl
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all/ar/test.jsonl
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{mono/all/en → all/ar}/train.jsonl
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{mono/all/en → all/ar}/validation.jsonl
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all/az/test.jsonl
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all/az/train.jsonl
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all/az/validation.jsonl
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all/bn/test.jsonl
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all/bn/validation.jsonl
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all/cs/test.jsonl
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all/de/test.jsonl
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