def METHOD_NAME():
    from rasa_nlu.emulators.dialogflow import DialogflowEmulator
    em = DialogflowEmulator()
    data = {
        "text": "I want italian food",
        "intent": {"name": "inform", "confidence": 0.4794813722432127},
        "entities": [{"entity": "cuisine", "value": "italian", "start": 7, "end": 14}]
    }
    norm = em.normalise_response_json(data)
    assert norm == {
        "id": norm["id"],
        "result": {
            "action": None,
            "actionIncomplete": None,
            "contexts": [],
            "fulfillment": {},
            "metadata": {
                "intentId": norm["result"]["metadata"]["intentId"],
                "intentName": {
                    "confidence": data["intent"]["confidence"],
                    "name": data["intent"]["name"]
                },
                "webhookUsed": "false"
            },
            "parameters": {
                "cuisine": [
                    "italian"
                ]
            },
            "resolvedQuery": data["text"],
            "score": None,
            "source": "agent"
        },
        "sessionId": norm["sessionId"],
        "status": {
            "code": 200,
            "errorType": "success"
        },
        "timestamp": norm["timestamp"]
    }