{"id":628,"date":"2020-11-25T22:28:32","date_gmt":"2020-11-25T22:28:32","guid":{"rendered":"https:\/\/machine-learning.webcloning.com\/2020\/11\/25\/announcing-the-launch-of-amazon-comprehend-events\/"},"modified":"2020-11-25T22:28:32","modified_gmt":"2020-11-25T22:28:32","slug":"announcing-the-launch-of-amazon-comprehend-events","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2020\/11\/25\/announcing-the-launch-of-amazon-comprehend-events\/","title":{"rendered":"Announcing the launch of Amazon Comprehend Events"},"content":{"rendered":"
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Every day, financial organizations need to analyze news articles, SEC filings, and press releases, as well as track financial events such as bankruptcy announcements, changes in executive leadership at companies, and announcements of mergers and acquisitions. They want to accurately extract the key data points and associations among various people and organizations mentioned within an announcement to update their investment models in a timely manner. Traditional natural language processing services can extract entities such as people, organizations and locations from text, but financial analysts need more. They need to understand how these entities relate to each other in the text.<\/p>\n

Today, Amazon Comprehend<\/a> is launching Comprehend Events, a new API for event extraction from natural language text documents. With this launch, you can use Comprehend Events to extract granular details about real-world events and associated entities expressed in unstructured text. This new API allows you to answer who-what-when-where questions over large document sets, at scale and without prior NLP experience.<\/p>\n

This post gives an overview of the NLP capabilities that Comprehend Events supports, along with suggestions for processing and analyzing documents with this feature. We\u2019ll close with a discussion of several solutions that use Comprehend Events, such as knowledge base population, semantic search, and document triage, all of which can be developed with companion AWS services for storing, visualizing, and analyzing the predictions made by Comprehend Events.<\/p>\n

Comprehend Events overview<\/h2>\n

The Comprehend Events API, under the hood, converts unstructured text into structured data that answers who-what-when-where-how questions. Comprehend Events lets you extract the event structure from a document, distilling pages of text down to easily processed data for consumption by your AI applications or graph visualization tools. In the following figure, an Amazon press release announcing the 2017 acquisition of Whole Foods Market, Inc. is rendered as a graph showing the core semantics of the acquisition event, as well as the status of Whole Foods\u2019 CEO post merger.<\/p>\n

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Amazon (AMZN) today announced that they will acquire Whole Foods Market (WFM) for $42 per share in an all-cash transaction valued at approximately $13.7 billion, including Whole Foods Market\u2019s net debt. Whole Foods Market will continue to operate stores under the Whole Foods Market brand and source from trusted vendors and partners around the world. John Mackey will remain as CEO of Whole Foods Market and Whole Foods Market\u2019s headquarters will stay in Austin, Texas.<\/p>\n

From: Amazon Press Center Release Archive<\/a><\/p>\n<\/blockquote>\n


Extracted event triggers<\/strong> \u2013 Which events took place. In our example, CORPORATE_ACQUISITION<\/code> and EMPLOYMENT<\/code> events were detected. Not shown in the preceding figure, the API also returns which words in the text indicate the occurrence of the event, for example the words \u201cacquire\u201d and \u201ctransaction\u201d in the context of the document indicate that a CORPORATE_ACQUISITION<\/code> took place. The Comprehend Events API returns a variety of insights into the event semantics of a document:<\/p>\n