The Machine Readable Transcripts dataset aggregates data from earnings calls delivered in a machine-readable format for Natural Language Processing (NLP) applications with metadata tagging.

Leverage Machine Readable Transcripts to keep track of event information for specific companies including dates, times, dial-in and replay numbers and investor relations contact information. Easily combine data from earnings, M&A, guidance, shareholder, company conference presentations and special calls with traditional datasets to develop proprietary analytics.

With this dataset you can rely on:

• Seamless linking between the Speaker ID to the S&P Global Estimates and Professionals database to help identify sell-side analysts' revisions.
• Intraday updates via a feed or streaming XML messages for details on calls scheduled for transcription.
• 13,600+ entities under coverage with history going back up to 2004.

The dataset leverages the power of Kensho NERD to identify company names and aliases mentioned during earnings calls and specifies the mention location in the transcript.

[Awards]

• 2019 Data Management Insight Award for Best Proposition for AI, Machine Learning, Data Science
• 2020 Data Management Insight Award for Best Proposition for AI & Machine Learning