Entity extraction is a known process used in extraction of information. It assigns and determines the named entities under predefined categories. In many documents, spreadsheets, social media or different databases, the text usually occurs as unstructured data. Our tool is able to identify and determine entities – location, date, time, money, person, organization from that data. Every revealed entity contains assigned sentiment value. The process delivers a new and structured view on your unstructured data.
Each detected entity is also labeled with sentiment being inferred from the lexical context, representing the sentiment towards that entity within the sentence.
Our system detects following entity types:
| Entity Type | Example |
| LOCATION | California, America, England |
| DATE | Tomorrow, Monday, today, 2019-01-02 |
| TIME | Morning, 12:15 p.m. |
| MONEY | $33, £24.22 |
| PERSON | David Archu.., Amy Joh.., Joe |
| ORGANIZATION | Amazon, MSN, Adtech |
Each detected entity is being displayed with the sentiment value expressed towards it
Please choose one of the options to start!
