spaCy/spacy/lang/es/tokenizer_exceptions.py

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from ..tokenizer_exceptions import BASE_EXCEPTIONS
from ...symbols import ORTH, LEMMA, NORM, PRON_LEMMA
from ...util import update_exc
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_exc = {
"pal": [{ORTH: "pa", LEMMA: "para"}, {ORTH: "l", LEMMA: "el", NORM: "el"}],
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}
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for exc_data in [
{ORTH: "", LEMMA: "número"},
{ORTH: "°C", LEMMA: "grados Celcius"},
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{ORTH: "aprox.", LEMMA: "aproximadamente"},
{ORTH: "dna.", LEMMA: "docena"},
{ORTH: "dpto.", LEMMA: "departamento"},
{ORTH: "ej.", LEMMA: "ejemplo"},
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{ORTH: "esq.", LEMMA: "esquina"},
{ORTH: "pág.", LEMMA: "página"},
{ORTH: "p.ej.", LEMMA: "por ejemplo"},
{ORTH: "Ud.", LEMMA: PRON_LEMMA, NORM: "usted"},
{ORTH: "Vd.", LEMMA: PRON_LEMMA, NORM: "usted"},
{ORTH: "Uds.", LEMMA: PRON_LEMMA, NORM: "ustedes"},
{ORTH: "Vds.", LEMMA: PRON_LEMMA, NORM: "ustedes"},
{ORTH: "vol.", NORM: "volúmen"},
]:
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_exc[exc_data[ORTH]] = [exc_data]
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# Times
_exc["12m."] = [{ORTH: "12"}, {ORTH: "m.", LEMMA: "p.m."}]
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for h in range(1, 12 + 1):
for period in ["a.m.", "am"]:
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_exc[f"{h}{period}"] = [{ORTH: f"{h}"}, {ORTH: period, LEMMA: "a.m."}]
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for period in ["p.m.", "pm"]:
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_exc[f"{h}{period}"] = [{ORTH: f"{h}"}, {ORTH: period, LEMMA: "p.m."}]
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for orth in [
"a.C.",
"a.J.C.",
"d.C.",
"d.J.C.",
"apdo.",
"Av.",
"Avda.",
"Cía.",
"Dr.",
"Dra.",
"EE.UU.",
"etc.",
"fig.",
"Gob.",
"Gral.",
"Ing.",
"J.C.",
"km/h",
"Lic.",
"m.n.",
"núm.",
"P.D.",
"Prof.",
"Profa.",
"q.e.p.d.",
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"Q.E.P.D." "S.A.",
"S.L.",
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"S.R.L." "s.s.s.",
"Sr.",
"Sra.",
"Srta.",
]:
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_exc[orth] = [{ORTH: orth}]
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TOKENIZER_EXCEPTIONS = update_exc(BASE_EXCEPTIONS, _exc)