lang-model/naive-nlu/test.py

import json

from knowledge_base import KnowledgeBase

examples = [
    {
        "text": "icecream is cold",
        "parsed": ("exists-property-with-value", 'icecream', 'cold'),
    },
    {
        "text": "is icecream cold?",
        "parsed": ("question", ("exists-property-with-value", 'icecream', 'cold'))
    },
    {
        "text": "lava is dangerous",
        "parsed": ("exists-property-with-value", 'lava', 'dangerous')
    },
    # {
    #     "text": "is lava dangerous?",
    #     "parsed": ("question", ("exists-property-with-value", 'lava', 'dangerous')),
    # },
    # {
    #     "text": "earth is a planet",
    #     "parsed": ("pertenence-to-group", 'earth', 'planet'),
    # },
    # {
    #     "text": "is earth a moon?",
    #     "parsed": ("question", ("pertenence-to-group", 'earth', 'moon')),
    # },
    # {
    #     "text": "Green is a color",
    #     "parsed": ("pertenence-to-group", 'green', 'color'),
    # },
    # {
    #     "text": "a plane can fly",
    #     "parsed": ("has-capacity", 'plane', 'fly')
    # },
    # {
    #     "text": "a wale can swim",
    #     "parsed": ("has-capacity", 'wale', 'swim')
    # },
]

base_knowledge = {
    'icecream': {
        "groups": set(['noun', 'object', 'comestible', 'sweet']),
    },
    'lava': {
        "groups": set(['noun', 'object']),
    },
    'earth': {
        "groups": set(['noun', 'object', 'planet']),
    },
    'green': {
        "groups": set(['noun', 'color', 'concept']),
    },
    'plane': {
        "groups": set(['noun', 'object', 'vehicle', 'fast']),
    },
    'car': {
        "groups": set(['noun', 'object', 'vehicle', 'slow-ish']),
    },
    'wale': {
        "groups": set(['noun', 'object', 'living-being']),
    },
    'cold': {
        "groups": set(['property', 'temperature']),
        "as_property": "temperature",
    },
    'dangerous': {
        "groups": set(['property']),
        "as_property": "safety",
    },
    'planet': {
        "groups": set(['noun', 'group']),
    },
    'color': {
        "groups": set(['property', 'group']),
    },
    'fly': {
        "groups": set(['verb']),
    },
    'swim': {
        "groups": set(['verb']),
    },
}


def test_assumption(expectedResponse, knowledge, query):
    print("Query: {}".format(query['text']))
    print("Expected: {}".format(expectedResponse))

    result, abstract_tree, diff = knowledge.process(query['text'])
    print("\x1b[0;3{}mResult: {}\x1b[0m".format("1" if result != expectedResponse else "2", result))


def main():
    knowledge = KnowledgeBase(
        knowledge=base_knowledge,
    )

    differences = knowledge.train(examples)

    print("----")
    print(differences())
    print("----")

    test_assumption(True, knowledge, {'text': 'is lava dangerous?'})
    # for test in [{'text': 'a bus can run'}, {'text': 'io is a moon'}]:
    #     row = test['text']
    #     result, inferred_tree, differences = knowledge.process(row)

    #     print("result:", result)
    #     print(differences())
    #     print()
    # print('-----')
    # print(json.dumps(sorted(knowledge.knowledge.keys()), indent=4))
    # print('-----')
    # queryTrue = { "text": "is io a moon?", "parsed": ("question", ("pertenence-to-group", "io", "moon")) }
    # queryFalse = { "text": "is io a planet?", "parsed": ("question", ("pertenence-to-group", "io", "planet")) }

    # test_assumption(True, knowledge, queryTrue)
    # test_assumption(False, knowledge, queryFalse)

if __name__ == '__main__':
    main()