Natural Language Processing for the rest of us.
Opinions, Entities and Sentiments in 6 languages
and across domains.

The OpeNER project

OpeNER is a project funded by the European Commission under the FP7 (7th Framework Program). Its acronym stands for Open Polarity Enhanced Name Entity Recognition.

OpeNER’s main goal is to provide a set of ready to use tools to perform some natural language processing tasks, free and easy to adapt for Academia, Research and Small and Medium Enterprise to integrate them in their workflow. More precisely, OpeNER aims to be able to detect and disambiguate entity mentions and perform sentiment analysis and opinion detection on the texts, to be able for example, to extract the sentiment and the opinion of customers about certain resource (e.g. hotels and accommodations) in Web reviews.

What can OpeNER do?
OpeNER excels at detecting sentiments, opinions and named entities in texts. Get more information in the getting started guide.
Open Source
All source code of OpeNER is freely available and ready for you to use. Visit the Getting Started section to get some help on installing OpeNER on your local machine.
Jump right in and get started. All of OpeNER is available as a webservice.

Multi Lingual
OpeNER is currently available in Dutch, English, German, French, Spanish and Italian. Is your language not in the list? You can add it yourself if you want.
Tourism & News
The OpeNER components have been proven and tested on news and hospitality reviews. It is pretty easy however, to add your own domain.
There are well written manuals available on how to extend the OpeNER technology to your domain and in your languages. Visit the getting started page to get started.

Featured Demo

This demo was created to show you what the different OpeNER components can achieve. The demo uses the OpeNER Webservices to analyze it's texts. Visit the OpeNER Analysis Demo.

This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 261712.