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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
unit tests:
* extract the top-k entities from a raw text
see copyright/license https://huggingface.co/spaces/DerwenAI/textgraphs/blob/main/README.md
"""
from os.path import abspath, dirname
import pathlib
import sys
sys.path.insert(0, str(pathlib.Path(dirname(dirname(abspath(__file__))))))
import textgraphs # pylint: disable=C0413
def test_extract_herzog (
) -> None:
"""
Run an extract with the Werner Herzog blurb.
"""
text: str = """
Werner Herzog is a remarkable filmmaker and intellectual originally from Germany, the son of Dietrich Herzog.
"""
tg: textgraphs.TextGraphs = textgraphs.TextGraphs( # pylint: disable=C0103
factory = textgraphs.PipelineFactory(),
)
pipe: textgraphs.Pipeline = tg.create_pipeline(
text.strip(),
)
tg.collect_graph_elements(
pipe,
debug = False,
)
tg.perform_entity_linking(
pipe,
debug = False,
)
tg.construct_lemma_graph(
debug = False,
)
tg.calc_phrase_ranks(
debug = False,
)
results: list = [
( row["text"], row["pos"], )
for _, row in tg.get_phrases_as_df().iterrows()
]
# top-k, k=4
results = results[:4]
expects: list = [
("Germany", "PROPN"),
("Werner Herzog", "PROPN"),
("Dietrich Herzog", "PROPN"),
]
for pair in expects:
assert pair in results
if __name__ == "__main__":
test_extract_herzog()
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