rasahq--rasa/tests/nlu/utils/test_bilou_utils.py

import logging
from typing import Text, List, Optional
from _pytest.logging import LogCaptureFixture
import pytest

from rasa.nlu.tokenizers.whitespace_tokenizer import WhitespaceTokenizer
import rasa.nlu.utils.bilou_utils as bilou_utils
from rasa.nlu.constants import BILOU_ENTITIES
from rasa.shared.nlu.constants import ENTITIES
from rasa.shared.nlu.training_data.training_data import TrainingData
from rasa.shared.nlu.training_data.message import Message


@pytest.mark.parametrize(
    "tag, expected",
    [
        ("B-person", "person"),
        ("I-location", "location"),
        ("location", "location"),
        ("U-company", "company"),
        ("L-company", "company"),
    ],
)
def test_entity_name_from_tag(tag, expected):
    actual = bilou_utils.tag_without_prefix(tag)

    assert actual == expected


@pytest.mark.parametrize(
    "tag, expected",
    [
        ("B-person", "B-"),
        ("I-location", "I-"),
        ("location", None),
        ("U-company", "U-"),
        ("L-company", "L-"),
        ("O-company", None),
    ],
)
def test_bilou_from_tag(tag, expected):
    actual = bilou_utils.bilou_prefix_from_tag(tag)

    assert actual == expected


def test_tags_to_ids():
    message = Message.build(text="Germany is part of the European Union")
    message.set(
        BILOU_ENTITIES,
        ["U-location", "O", "O", "O", "O", "B-organisation", "L-organisation"],
    )

    tag_id_dict = {"O": 0, "U-location": 1, "B-organisation": 2, "L-organisation": 3}

    tags = bilou_utils.bilou_tags_to_ids(message, tag_id_dict)

    assert tags == [1, 0, 0, 0, 0, 2, 3]


def test_build_tag_id_dict():
    message_1 = Message.build(
        text="Germany is part of the European Union", intent="inform"
    )
    message_1.set(
        BILOU_ENTITIES,
        ["U-location", "O", "O", "O", "O", "B-organisation", "L-organisation"],
    )

    message_2 = Message.build(text="Berlin is the capital of Germany", intent="inform")
    message_2.set(BILOU_ENTITIES, ["U-location", "O", "O", "O", "O", "U-location"])

    training_data = TrainingData([message_1, message_2])

    tag_id_dict = bilou_utils.build_tag_id_dict(training_data)

    assert tag_id_dict == {
        "O": 0,
        "B-location": 1,
        "I-location": 2,
        "L-location": 3,
        "U-location": 4,
        "B-organisation": 5,
        "I-organisation": 6,
        "L-organisation": 7,
        "U-organisation": 8,
    }


def test_apply_bilou_schema(whitespace_tokenizer: WhitespaceTokenizer):

    message_1 = Message.build(
        text="Germany is part of the European Union", intent="inform"
    )
    message_1.set(
        ENTITIES,
        [
            {"start": 0, "end": 7, "value": "Germany", "entity": "location"},
            {
                "start": 23,
                "end": 37,
                "value": "European Union",
                "entity": "organisation",
            },
        ],
    )

    message_2 = Message.build(text="Berlin is the capital of Germany", intent="inform")
    message_2.set(
        ENTITIES,
        [
            {"start": 0, "end": 6, "value": "Berlin", "entity": "location"},
            {"start": 25, "end": 32, "value": "Germany", "entity": "location"},
        ],
    )

    training_data = TrainingData([message_1, message_2])

    whitespace_tokenizer.process_training_data(training_data)

    bilou_utils.apply_bilou_schema(training_data)

    assert message_1.get(BILOU_ENTITIES) == [
        "U-location",
        "O",
        "O",
        "O",
        "O",
        "B-organisation",
        "L-organisation",
    ]
    assert message_2.get(BILOU_ENTITIES) == [
        "U-location",
        "O",
        "O",
        "O",
        "O",
        "U-location",
    ]


@pytest.mark.parametrize(
    "tags, confidences, expected_tags, expected_confidences, debug_message",
    [
        (
            ["O", "B-person", "I-person", "L-person", "O", "U-person", "O"],
            [0.99, 0.89, 0.93, 0.99, 0.89, 0.97, 0.87],
            ["O", "B-person", "I-person", "L-person", "O", "U-person", "O"],
            [0.99, 0.89, 0.93, 0.99, 0.89, 0.97, 0.87],
            None,
        ),
        (
            ["O", "B-person", "B-location", "I-location", "O"],
            [0.99, 0.89, 0.93, 0.78, 0.89],
            ["O", "U-person", "B-location", "L-location", "O"],
            [0.99, 0.89, 0.93, 0.78, 0.89],
            "B- tag not closed",
        ),
        (
            ["O", "B-person", "I-location", "L-person"],
            [0.99, 0.89, 0.77, 0.87],
            ["O", "B-person", "I-person", "L-person"],
            [0.99, 0.89, 0.76, 0.87],
            "B- tag, L- tag pair encloses multiple entity classes",
        ),
        (
            ["O", "B-person", "I-location", "L-location"],
            [0.99, 0.78, 0.93, 0.96],
            ["O", "B-location", "I-location", "L-location"],
            [0.99, 0.79, 0.93, 0.96],
            "B- tag, L- tag pair encloses multiple entity classes",
        ),
        (
            ["O", "B-person", "I-location", "L-location"],
            [0.99, 0.99, 0.77, 0.77],
            ["O", "B-location", "I-location", "L-location"],
            [0.99, 0.72, 0.77, 0.77],
            "B- tag, L- tag pair encloses multiple entity classes",
        ),
        (
            ["O", "B-person", "I-location", "L-location", "B-person", "L-person"],
            [0.99, 0.78, 0.93, 0.96, 0.93, 0.96],
            ["O", "B-location", "I-location", "L-location", "B-person", "L-person"],
            [0.99, 0.79, 0.93, 0.96, 0.93, 0.96],
            "B- tag, L- tag pair encloses multiple entity classes",
        ),
        (
            ["O", "B-person", "O"],
            [0.99, 0.89, 0.87],
            ["O", "U-person", "O"],
            [0.99, 0.89, 0.87],
            "B- tag not closed",
        ),
        (
            ["O", "B-person"],
            [0.99, 0.89],
            ["O", "U-person"],
            [0.99, 0.89],
            "B- tag not closed",
        ),
        (
            ["O", "B-person", "I-person"],
            [0.99, 0.89, 0.87],
            ["O", "B-person", "L-person"],
            [0.99, 0.89, 0.87],
            "B- tag not closed",
        ),
        (
            ["O", "B-person", "I-location"],
            [0.99, 0.89, 0.78],
            ["O", "B-person", "L-person"],
            [0.99, 0.89, 0.64],
            "B- tag not closed",
        ),
        (
            ["O", "B-person", "B-location"],
            [0.99, 0.89, 0.89],
            ["O", "U-person", "U-location"],
            [0.99, 0.89, 0.89],
            "B- tag not closed",
        ),
    ],
)
def test_check_consistent_bilou_tagging(
    tags: List[Text],
    confidences: List[float],
    expected_tags: List[Text],
    expected_confidences: List[float],
    debug_message: Optional[Text],
    caplog: LogCaptureFixture,
):

    with caplog.at_level(logging.DEBUG):
        actual_tags, actual_confidences = bilou_utils.ensure_consistent_bilou_tagging(
            tags, confidences
        )

    if debug_message:
        assert len(caplog.records) > 0
        assert debug_message in caplog.text
    else:
        assert len(caplog.records) == 0

    assert actual_tags == expected_tags
    assert actual_confidences == expected_confidences