calais

And Calais is a lot of machinery to involve just to extract entities from a page of text.

I used Open Calais two years ago for a project, and would definitely use it again if needed.

One Green councillor who organised a public meeting about the transportation of animals from Calais to Dover is understood to be on it.

I have family in Nord Pas De Calais who dip it in their coffee in the morning.

And further from [1]: > The migrants in Calais all have one thing in common: they come from countries that were colonised by Britain.

By the time the tank ran dry, Ford had covered 1,013 miles and got to within 70 miles of Calais on the return route.

There are almost no refugees in Calais from former French colonies.

There are automated services that let you do this, I've used Open Calais and MetaCarta in the past with great results.

They can pass them, but they'd almost certainly be as unconstitutional as a law from 1944 that mandated the invasion of Calais rather than Normandy.

Migrants in Calais trying to get to the UK.

One thing that Open Calais does that I really like is that they attempt to have a single URI uniquely identifying recognized named entities.

Edit: I use the Wikipedia text for NLP experiments, including finding entities (my own code) and processing with both Open Calais and Standford NLP libraries.

There is a city in northern France called "Pas de Calais", which roughly means the "steps" or entrance of Calais (there's a strait, and the Allies successfully fooled the Germans into thinking it would be the D-Day landing site).

For a time, while not knowing that "pas" also meant "step" I wondered why in the world anyone would name a city "not from Calais".

I'm not sure exactly what you mean, are you talking about entity extraction with confidence levels ala Calais?

Go and read about what is done to afghani refugees in Calais.

The numbers arriving in Italy and Greece are orders of magnitude higher that those living in the shanty in Calais, hoping to come to the UK.