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Named Entity extraction (NER) is a technique used to extract textual entities from a body of text.
With our Entity Extractor you can fast and easy find entities such as date, location, organization, and named persons. Entities are also often used as input data for other features such as query completion and “did you mean” spell checking.
Translate any text you want with our Translator; we support ~100 languages. Please note that the expected time for processing a request can be 10-30 seconds during the beta testing period.
Get the important facts and ideas highlighted in an executive summary by our Summarizer.
We have trained the Summarizer on a significant volume of news articles and it's an English-speaking bleeding edge tech solution. Summarizing language models come in two varieties: extractive and abstractive. Our main model is abstractive, meaning that it can write new sentences in addition to extracting the most relevant ones from the text.
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