generic_rasa_train_data.json

{
  "rasa_nlu_data": {
    "regex_features": [
      {
        "name": "greet",
        "pattern": "^hey|^hi"
      }
    ],
    "entity_synonyms": [
      {
        "value": "chinese",
        "synonyms": ["Chinese", "Chines", "chines"]
      }
    ],
    "common_examples": [
      {
        "text": "hey", 
        "intent": "greet", 
        "entities": []
      }, 
      {
        "text": "howdy", 
        "intent": "greet", 
        "entities": []
      },
      {
        "text": "what's up",
        "intent": "greet",
        "entities": []
      },
      {
        "text": "hi, whats up",
        "intent": "greet",
        "entities": []
      },
      {
        "text": "hi bot, what's up",
        "intent": "greet",
        "entities": []
      },
      {
        "text": "hi bot",
        "intent": "greet",
        "entities": []
      },
      {
        "text": "hey there",
        "intent": "greet", 
        "entities": []
      }, 
      {
        "text": "hello", 
        "intent": "greet", 
        "entities": []
      }, 
      {
        "text": "hi", 
        "intent": "greet", 
        "entities": []
      },
      {
        "text": "good morning",
        "intent": "greet",
        "entities": []
      },
      {
        "text": "good evening",
        "intent": "greet",
        "entities": []
      },
      {
        "text": "dear sir",
        "intent": "greet",
        "entities": []
      },
      {
        "text": "yes", 
        "intent": "affirm", 
        "entities": []
      }, 
      {
        "text": "yep", 
        "intent": "affirm", 
        "entities": []
      }, 
      {
        "text": "yeah", 
        "intent": "affirm", 
        "entities": []
      },
      {
        "text": "indeed",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "that's right",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "ok",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "great",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "right, thank you",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "correct",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "great choice",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "sounds really good",
        "intent": "affirm",
        "entities": []
      },
      {
        "text": "bye", 
        "intent": "goodbye", 
        "entities": []
      }, 
      {
        "text": "goodbye", 
        "intent": "goodbye", 
        "entities": []
      }, 
      {
        "text": "good bye", 
        "intent": "goodbye", 
        "entities": []
      }, 
      {
        "text": "stop", 
        "intent": "goodbye", 
        "entities": []
      }, 
      {
        "text": "end", 
        "intent": "goodbye", 
        "entities": []
      },
      {
        "text": "farewell",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "Bye bye",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "have a good one",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "good day sir",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "goodbye, have a good day sir",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "goodbye, have a good day ma'am",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "thanks, goodbye bot",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "good day bot",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "good day",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "i'm leaving",
        "intent": "goodbye",
        "entities": []
      },
      {
        "text": "i'm looking for a place to eat",
        "intent": "None",
        "entities": []
      },
      {
        "text": "I want to grab lunch",
        "intent": "None",
        "entities": []
      },
      {
        "text": "I am searching for a dinner spot",
        "intent": "None",
        "entities": []
      },
      {
        "text": "i'm looking for a place in the north of town",
        "intent": "None",
        "entities": []
      },
      {
        "text": "show me chinese restaurants",
        "intent": "None",
        "entities": []
      },
      {
        "text": "show me chines restaurants in the north",
        "intent": "None",
        "entities": []
      },
      {
        "text": "show me a mexican place in the centre", 
        "intent": "None", 
        "entities": []
      },
      {
        "text": "i am looking for an indian spot called olaolaolaolaolaola",
        "intent": "None",
        "entities": []
      },     {
        "text": "search for restaurants",
        "intent": "None",
        "entities": []
      },
      {
        "text": "anywhere in the west",
        "intent": "None",
        "entities": []
      },
      {
        "text": "anywhere near 18328",
        "intent": "None",
        "entities": []
      },
      {
        "text": "I am looking for asian fusion food",
        "intent": "None",
        "entities": []
      },
      {
        "text": "I am looking a restaurant in 29432",
        "intent": "None",
        "entities": []
      },
      {
        "text": "I am looking for mexican indian fusion",
        "intent": "None",
        "entities": []
      },
      {
        "text": "central indian restaurant",
        "intent": "None",
        "entities": []
      },
      {
        "text": "Niels Bohr and John Archibald Wheeler applied the liquid drop model of the atomic nucleus to explain the mechanism of nuclear fission",
        "intent": "None",
        "entities": []
      },
      {
        "text": "As the experimental physicists studied fission, they uncovered puzzling results.",
        "intent": "None",
        "entities": []
      },
      {
        "text": "George Placzek asked Bohr why uranium seemed to fission with both fast and slow neutrons.",
        "intent": "None",
        "entities": []
      },
      {
        "text": "Walking to a meeting with Wheeler, Bohr had an insight that the fission at low energies was due to the uranium-235 isotope, while at high energies it was mainly due to the far more abundant uranium-238 isotope.",
        "intent": "None",
        "entities": []
      },
      {
        "text": "Gaseous diffusion is based on Graham's law, which states that the rate of effusion of a gas through a porous barrier is inversely proportional to the square root of the gas's molecular mass.",
        "intent": "None",
        "entities": []
      },
      {
        "text": "Booth, Dunning and von Grosse investigated the gaseous diffusion process.",
        "intent": "None",
        "entities": []
      },
      {
        "text": "Gaseous diffusion had been used to separate isotopes before.",
        "intent": "None",
        "entities": []
      }
    ]
  }
}