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PreciseClaimsExtraction

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metadata
license: mit
tags:
  - infinite-dataset-hub
  - synthetic

PreciseClaimsExtraction

tags: entity extraction, information retrieval, exact match

Note: This is an AI-generated dataset so its content may be inaccurate or false

Dataset Description: The 'PreciseClaimsExtraction' dataset is designed for the task of extracting exact sentences from paragraphs that make specific claims or assertions. Each row in the dataset contains a paragraph of text followed by a list of sentences that are considered precise claims within that paragraph. The 'labels' column contains an identifier for the type of claim or the nature of the information that the sentence conveys.

CSV Content Preview:

paragraph,sentence,labels
"Global warming is accelerating due to human activities.","Global warming is accelerating due to human activities.","ClimateChangeClaim"
"A study from 2020 found that certain species are adapting to climate change.","A study from 2020 found that certain species are adapting to climate change.","ScientificClaim"
"Deforestation contributes significantly to carbon emissions.","Deforestation contributes significantly to carbon emissions.","EnvironmentalImpactClaim"
"The International Space Station has been continuously inhabited since 2000.","The International Space Station has been continuously inhabited since 2000.","SpaceStationFact"
"Vaccines are critical in preventing infectious diseases.","Vaccines are critical in preventing infectious diseases.","HealthScienceClaim"

The above CSV represents a snippet of what the 'PreciseClaimsExtraction' dataset might look like, with precise claims extracted from paragraphs and associated labels that categorize the type of claim. Each label is unique and specific to the nature of the claim, providing additional context for machine learning models focused on entity extraction, information retrieval, or tasks requiring exact match identification.

Source of the data:

The dataset was generated using the Infinite Dataset Hub and microsoft/Phi-3-mini-4k-instruct using the query '':