def test_roundtrip_offsets_biluo_conversion(en_tokenizer):
text = "I flew to Silicon Valley via London."
biluo_tags = ["O", "O", "O", "B-LOC", "L-LOC", "O", "U-GPE", "O"]
offsets = [(10, 24, "LOC"), (29, 35, "GPE")]
doc = en_tokenizer(text)
biluo_tags_converted = offsets_to_biluo_tags(doc, offsets)
assert biluo_tags_converted == biluo_tags
offsets_converted = biluo_tags_to_offsets(doc, biluo_tags)
offsets_converted = [ent for ent in offsets if ent[2]]
assert offsets_converted == offsets
def offsets_from_tags(
doc: Doc,
tags: List[str],
label_encoding: Optional[str] = "BIOUL",
only_token_spans: bool = False,
) -> List[Dict]:
"""Converts BIOUL or BIO tags to offsets
Parameters
----------
doc
A spaCy Doc created with `text` and the backbone tokenizer
tags
A list of BIOUL or BIO tags
label_encoding
The label encoding of the tags: BIOUL or BIO
only_token_spans
If True, offsets contains only token index references. Default is False
Returns
-------
offsets
A list of dicts with start and end character/token index with respect to the doc and the span label:
`{"start": int, "end": int, "start_token": int, "end_token": int, "label": str}`
"""
# spacy's biluo_tags_to_offsets surprisingly does not check this ...
if len(doc) != len(tags):
raise ValueError(
f"Number of tokens and tags must be the same, "
f"but 'len({list(doc)}) != len({tags})"
)
if label_encoding == "BIO":
tags = to_bioul(tags, encoding="BIO")
offsets = []
for start, end, label in biluo_tags_to_offsets(doc, tags):
span = doc.char_span(start, end)
data = {
"start_token": span.start,
"end_token": span.end,
"label": label,
}
if not only_token_spans:
data.update({"start": start, "end": end})
offsets.append(data)
return offsets
