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AWS Launches Amazon Comprehend Events — A New API For Event Extraction

AWS Launches Amazon Comprehend Events — A New API For Event Extraction

AWS Launches Amazon Comprehend Events — A New API For Event Extraction

In an attempt to help financial organisations track financial events, AWS has announced the launch of Amazon Comprehend Events — a new API for event extraction from natural language text documents.

According to the official blog post of the release, financial organisations need to analyse several documents, news articles, press releases, as well as track financial events such as bankruptcy announcements, new appointments and M&A announcements, which requires to extract accurate data points. This allows them to update their investment models in a timely manner. Traditional natural language processing services can he relationship between these entities they required an advanced tool. Thus, Amazon Comprehend releases this new API for extracting events from natural language text documents.

With this launch, the companies can now use the API — Comprehend Events — to pull out necessary details about financial events and associated entities in various texts. This new API will allow individuals to answer the who-what-when-where questions in document sets without prior NLP experience.

Explaining better, the blog post stated — The Comprehend Events API converts unstructured text into structured data to answer the necessary details of the documents. It further allows the users to extract the event structure from a document, distilling pages of text down to easily processed data for consumption.



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This will help the financial organisation to extract event triggers, entity mentions, event argument role, groups of coreferential event triggers, and groups of coreferential entity mentions. Currently, the Comprehend Events API is available as an asynchronous API supporting the extraction of a fixed set of event types in the finance domain, such as Corporate acquisition and IPOs, stock code and monetary value, investors, offering date, and employer, and others such.

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