InsuranceQA V2: Question Answering Dataset for Insurance Domain

A dataset released as part of a 2015 IEEE ASRU workshop paper by Feng, Minwei, et al. titled 'Applying deep learning to answer selection: A study and an open task.' The data was deconstructed from tokens provided in a GitHub repository by the user 'deccan-ai'.

Use Cases

• Train answer selection models based on the question-answer pairs described.
• Benchmark deep learning architectures for natural language understanding tasks based on the described open task.
• Develop domain-specific QA systems for insurance applications based on the described content.

Strengths

• Dataset originates from a peer-reviewed 2015 IEEE ASRU workshop paper.
• Data was deconstructed from a publicly available GitHub repository.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Feng, Minwei, et al. (2015 IEEE ASRU workshop).

Collection Method

Deconstructed from tokens provided in a GitHub repository.

Freshness

Last updated 2024-03-20 12:47:01; freshness should be verified.