README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
language:
  - en
multilinguality:
  - monolingual
size_categories:
  - 1M<n<10M
task_categories:
  - feature-extraction
  - sentence-similarity
pretty_name: Quora Duplicate Questions
tags:
  - sentence-transformers
dataset_info:
  - config_name: pair
    features:
      - name: anchor
        dtype: string
      - name: positive
        dtype: string
    splits:
      - name: train
        num_bytes: 19063882.986566573
        num_examples: 149263
    download_size: 10710908
    dataset_size: 19063882.986566573
  - config_name: pair-class
    features:
      - name: sentence1
        dtype: string
      - name: sentence2
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': different
              '1': duplicate
    splits:
      - name: train
        num_bytes: 54870273
        num_examples: 404290
    download_size: 34965546
    dataset_size: 54870273
  - config_name: triplet
    features:
      - name: anchor
        dtype: string
      - name: positive
        dtype: string
      - name: negative
        dtype: string
    splits:
      - name: train
        num_bytes: 17575186
        num_examples: 101762
    download_size: 10954551
    dataset_size: 17575186
  - config_name: triplet-all
    features:
      - name: anchor
        dtype: string
      - name: positive
        dtype: string
      - name: negative
        dtype: string
    splits:
      - name: train
        num_bytes: 483971801
        num_examples: 2792280
    download_size: 104682424
    dataset_size: 483971801
configs:
  - config_name: pair
    data_files:
      - split: train
        path: pair/train-*
  - config_name: pair-class
    data_files:
      - split: train
        path: pair-class/train-*
  - config_name: triplet
    data_files:
      - split: train
        path: triplet/train-*
  - config_name: triplet-all
    data_files:
      - split: train
        path: triplet-all/train-*

Dataset Card for Quora Duplicate Questions

This dataset contains the Quora Question Pairs dataset in four formats that are easily used with Sentence Transformers to train embedding models. The data was originally created by Quora for this Kaggle Competition.

Dataset Subsets

pair-class subset

• Columns: "sentence1", "sentence2", "label"
• Column types: str, str, class with {"0": "different", "1": "duplicate"}
• Examples:

  {
    'sentence1': 'What is the step by step guide to invest in share market in india?',
    'sentence2': 'What is the step by step guide to invest in share market?',
    'label': 0,
  }
  

• Collection strategy: A direct copy of Quora, but with more conveniently parsable columns.
• Deduplified: No

pair subset

• Columns: "anchor", "positive"
• Column types: str, str
• Examples:

  {
    'anchor': 'Astrology: I am a Capricorn Sun Cap moon and cap rising...what does that say about me?',
    'positive': "I'm a triple Capricorn (Sun, Moon and ascendant in Capricorn) What does this say about me?",
  }
  

• Collection strategy: Filtering away the "different" options from the pair-class subset, removing the label column, and renaming the columns.
• Deduplified: No

triplet-all subset

• Columns: "anchor", "positive", "negative"
• Column types: str, str, str
• Examples:

  {
    'anchor': 'Why in India do we not have one on one political debate as in USA?",
    'positive': 'Why cant we have a public debate between politicians in India like the one in US?',
    'negative': 'Can people on Quora stop India Pakistan debate? We are sick and tired seeing this everyday in bulk?',
  }
  

• Collection strategy: Taken from embedding-training-data, which states: "Duplicate question pairs from Quora with additional hard negatives (mined & denoised by cross-encoder)". Then, take all possible triplet pairs.
• Deduplified: No

triplet subset

• Columns: "anchor", "positive", "negative"
• Column types: str, str, str
• Examples:

  {
    'anchor': 'Why in India do we not have one on one political debate as in USA?",
    'positive': 'Why cant we have a public debate between politicians in India like the one in US?',
    'negative': 'Can people on Quora stop India Pakistan debate? We are sick and tired seeing this everyday in bulk?',
  }
  

• Collection strategy: Taken from embedding-training-data, which states: "Duplicate question pairs from Quora with additional hard negatives (mined & denoised by cross-encoder)". Then, take the anchor, positive and the first negative of each sample.
• Deduplified: No