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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  dataset_info:
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  features:
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  - name: topic_id
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  dtype: string
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  - name: answer
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  dtype: string
 
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  splits:
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  - name: train
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- num_bytes: 4327400
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  num_examples: 9176
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  - name: validation
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- num_bytes: 1066112
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  num_examples: 2313
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- download_size: 581860
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- dataset_size: 5393512
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  ---
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- # Dataset Card for "conv_ai_3_ru"
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- [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ annotations_creators:
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+ - crowdsourced
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+ language_creators:
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+ - translated
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+ language:
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+ - ru
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+ license:
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+ - unknown
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets:
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+ - conv_ai_3
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+ task_categories:
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+ - conversational
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+ - text-classification
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+ task_ids:
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+ - text-scoring
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+ paperswithcode_id: null
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+ pretty_name: conv_ai_3 (ru)
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+ tags:
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+ - evaluating-dialogue-systems
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  dataset_info:
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  features:
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  - name: topic_id
 
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  dtype: string
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  - name: answer
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  dtype: string
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+ config_name: conv_ai_3
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  splits:
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  - name: train
 
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  num_examples: 9176
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  - name: validation
 
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  num_examples: 2313
 
 
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  ---
 
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+ # Dataset Card for d0rj/conv_ai_3_ru
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** https://github.com/aliannejadi/ClariQ
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+ - **Repository:** https://github.com/aliannejadi/ClariQ
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+ - **Paper:** https://arxiv.org/abs/2009.11352
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+
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+ ### Dataset Summary
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+
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+ This is translated version of [conv_ai_3](https://huggingface.co/datasets/conv_ai_3) dataset to Russian language.
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+
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+ ### Languages
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+
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+ Russian (translated from English).
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+
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+ ## Dataset Structure
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+
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+ ### Data Fields
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+
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+ - `topic_id`: the ID of the topic (`initial_request`).
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+ - `initial_request`: the query (text) that initiates the conversation.
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+ - `topic_desc`: a full description of the topic as it appears in the TREC Web Track data.
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+ - `clarification_need`: a label from 1 to 4, indicating how much it is needed to clarify a topic. If an `initial_request` is self-contained and would not need any clarification, the label would be 1. While if a `initial_request` is absolutely ambiguous, making it impossible for a search engine to guess the user's right intent before clarification, the label would be 4.
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+ - `facet_id`: the ID of the facet.
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+ - `facet_desc`: a full description of the facet (information need) as it appears in the TREC Web Track data.
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+ - `question_id`: the ID of the question..
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+ - `question`: a clarifying question that the system can pose to the user for the current topic and facet.
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+ - `answer`: an answer to the clarifying question, assuming that the user is in the context of the current row (i.e., the user's initial query is `initial_request`, their information need is `facet_desc`, and `question` has been posed to the user).
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+
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+ ### Citation Information
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+
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+ @misc{aliannejadi2020convai3,
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+ title={ConvAI3: Generating Clarifying Questions for Open-Domain Dialogue Systems (ClariQ)},
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+ author={Mohammad Aliannejadi and Julia Kiseleva and Aleksandr Chuklin and Jeff Dalton and Mikhail Burtsev},
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+ year={2020},
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+ eprint={2009.11352},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+
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+ ### Contributions
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+
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+ Thanks to [@rkc007](https://github.com/rkc007) for adding this dataset.