nlp-intent-toolkit's Introduction

nlp-intent-toolkit

Recognizing intents with slots using OpenNLP.

This is an example of using OpenNLP to train a system to accept natural language input, particularly via a speech-to-text source, and return a recognized action with arguments. The system uses document categorization to determine the action for inputs and entity recognition to determine the arguments. The training system requires a directory containing separate files for each possible action, in this case the actions in a fictitious weather application:

- example/weather/train
  - current-weather.txt - get the current weather
  - hourly-forecast.txt - get the hourly forcast
  - five-day-forecast.txt - get a five day forecast

Each training file contains one example per line with any possible arguments surrounded by mark up to indicate the name of the parameter:

file: five-day-forecast.txt
...
how dos the weather look for this Thursday in <START:city> Boston <END>
is it going to snow this week in <START:city> Chicago <END>
show me the forecast for <START:city> Denver <END>
...

Running the Example

The training systems is run passing in the training file directory and any parameter name used in the training files.

$ mvn clean compile exec:java  -Dexec.args="example/weather/train city"
...
Training complete. Ready.

>show me the weather for chicago
action=current-weather args={ city=chicago }

>will it rain tonight
action=hourly-forecast args={ }

>how does it look in seattle
action=hourly-forecast args={ }

>what are the conditions in new york
action=current-weather args={ city=new york }

>how does this weekend look in boston
action=five-day-forecast args={ city=boston }

>give me the five day forecast
action=five-day-forecast args={ }

Recommend Projects

ikwattro / nlp-intent-toolkit Goto Github PK