mirror of https://github.com/explosion/spaCy.git
82 lines
2.1 KiB
Python
82 lines
2.1 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ...symbols import ORTH, LEMMA, TAG, NORM, ADP, DET
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from ...deprecated import PRON_LEMMA
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_exc = {
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"al": [
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{ORTH: "a", LEMMA: "a", TAG: ADP},
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{ORTH: "l", LEMMA: "el", TAG: DET}],
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"consigo": [
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{ORTH: "con", LEMMA: "con"},
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{ORTH: "sigo", LEMMA: PRON_LEMMA, NORM: "sí"}],
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"conmigo": [
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{ORTH: "con", LEMMA: "con"},
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{ORTH: "migo", LEMMA: PRON_LEMMA, NORM: "mí"}],
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"contigo": [
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{ORTH: "con", LEMMA: "con"},
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{ORTH: "tigo", LEMMA: PRON_LEMMA, NORM: "ti"}],
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"del": [
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{ORTH: "de", LEMMA: "de", TAG: ADP},
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{ORTH: "l", LEMMA: "el", TAG: DET}],
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"pel": [
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{ORTH: "pe", LEMMA: "per", TAG: ADP},
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{ORTH: "l", LEMMA: "el", TAG: DET}],
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"pal": [
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{ORTH: "pa", LEMMA: "para"},
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{ORTH: "l", LEMMA: "el"}],
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"pala": [
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{ORTH: "pa", LEMMA: "para"},
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{ORTH: "la"}]
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}
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for exc_data in [
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{ORTH: "aprox.", LEMMA: "aproximadamente"},
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{ORTH: "dna.", LEMMA: "docena"},
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{ORTH: "esq.", LEMMA: "esquina"},
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{ORTH: "pág.", LEMMA: "página"},
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{ORTH: "p.ej.", LEMMA: "por ejemplo"},
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{ORTH: "Ud.", LEMMA: PRON_LEMMA, NORM: "usted"},
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{ORTH: "Vd.", LEMMA: PRON_LEMMA, NORM: "usted"},
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{ORTH: "Uds.", LEMMA: PRON_LEMMA, NORM: "ustedes"},
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{ORTH: "Vds.", LEMMA: PRON_LEMMA, NORM: "ustedes"}]:
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_exc[exc_data[ORTH]] = [dict(exc_data)]
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# Times
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_exc["12m."] = [
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{ORTH: "12"},
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{ORTH: "m.", LEMMA: "p.m."}]
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for h in range(1, 12 + 1):
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for period in ["a.m.", "am"]:
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_exc["%d%s" % (h, period)] = [
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{ORTH: "%d" % h},
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{ORTH: period, LEMMA: "a.m."}]
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for period in ["p.m.", "pm"]:
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_exc["%d%s" % (h, period)] = [
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{ORTH: "%d" % h},
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{ORTH: period, LEMMA: "p.m."}]
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for orth in [
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"a.C.", "a.J.C.", "apdo.", "Av.", "Avda.", "Cía.", "etc.", "Gob.", "Gral.",
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"Ing.", "J.C.", "Lic.", "m.n.", "no.", "núm.", "P.D.", "Prof.", "Profa.",
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"q.e.p.d.", "S.A.", "S.L.", "s.s.s.", "Sr.", "Sra.", "Srta."]:
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_exc[orth] = [{ORTH: orth}]
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TOKENIZER_EXCEPTIONS = dict(_exc)
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