Hello, you could use the name finder to detect the time, location and food in the query.
For the classification of the order type you could train a maxent model which detects the order type. You should do the training with a couple of hundred samples to start with per language. Jörn On 11/20/11 8:34 AM, Eldad Yamin wrote:
HI, I'm wondering if anyone had an experience with using OpenNLP as a search engine input parser. For example, let's imagine that a restaurant wants to have a search engine in their site. their users can write things like: "Pizza to 12:00, delivery to my house at London" -> food: pizza, time: 12:00, order type: delivery, location: London" "Pasta, Apple pie, reservation, 14:00 (outside/smoking)." -> food: pasta, apple pie, time:14:00, order type: reservation, location: outside" "Smoking area, reservation to 12:00" -> "order type: reservation: , time: 12:00, location: outside/smoking area" In addition, it should be multilingual (I.e. German, French etc). I have the entities translated into different languages (I.e EN:reservation -> FR:réservation). Please advise. Thanks!
