spaCy/spacy/lang/nl/lemmatizer.py

121 lines
4.2 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from ...lemmatizer import Lemmatizer
from ...symbols import NOUN, VERB, ADJ, NUM, DET, PRON, ADP, AUX, ADV
class DutchLemmatizer(Lemmatizer):
# Note: CGN does not distinguish AUX verbs, so we treat AUX as VERB.
univ_pos_name_variants = {
NOUN: "noun",
"NOUN": "noun",
"noun": "noun",
VERB: "verb",
"VERB": "verb",
"verb": "verb",
AUX: "verb",
"AUX": "verb",
"aux": "verb",
ADJ: "adj",
"ADJ": "adj",
"adj": "adj",
ADV: "adv",
"ADV": "adv",
"adv": "adv",
PRON: "pron",
"PRON": "pron",
"pron": "pron",
DET: "det",
"DET": "det",
"det": "det",
ADP: "adp",
"ADP": "adp",
"adp": "adp",
NUM: "num",
"NUM": "num",
"num": "num",
}
def __call__(self, string, univ_pos, morphology=None):
# Difference 1: self.rules is assumed to be non-None, so no
# 'is None' check required.
# String lowercased from the get-go. All lemmatization results in
# lowercased strings. For most applications, this shouldn't pose
# any problems, and it keeps the exceptions indexes small. If this
# creates problems for proper nouns, we can introduce a check for
# univ_pos == "PROPN".
string = string.lower()
try:
univ_pos = self.univ_pos_name_variants[univ_pos]
except KeyError:
# Because PROPN not in self.univ_pos_name_variants, proper names
# are not lemmatized. They are lowercased, however.
return [string]
# if string in self.lemma_index.get(univ_pos)
index_table = self.lookups.get_table("lemma_index", {})
lemma_index = index_table.get(univ_pos, {})
# string is already lemma
if string in lemma_index:
return [string]
exc_table = self.lookups.get_table("lemma_exc", {})
exceptions = exc_table.get(univ_pos, {})
# string is irregular token contained in exceptions index.
try:
lemma = exceptions[string]
return [lemma[0]]
except KeyError:
pass
# string corresponds to key in lookup table
lookup_table = self.lookups.get_table("lemma_lookup", {})
looked_up_lemma = lookup_table.get(string)
if looked_up_lemma and looked_up_lemma in lemma_index:
return [looked_up_lemma]
rules_table = self.lookups.get_table("lemma_rules", {})
forms, is_known = self.lemmatize(
string, lemma_index, exceptions, rules_table.get(univ_pos, [])
)
# Back-off through remaining return value candidates.
if forms:
if is_known:
return forms
else:
for form in forms:
if form in exceptions:
return [form]
if looked_up_lemma:
return [looked_up_lemma]
else:
return forms
elif looked_up_lemma:
return [looked_up_lemma]
else:
return [string]
# Overrides parent method so that a lowercased version of the string is
# used to search the lookup table. This is necessary because our lookup
# table consists entirely of lowercase keys.
def lookup(self, string, orth=None):
lookup_table = self.lookups.get_table("lemma_lookup", {})
string = string.lower()
if orth is not None:
return lookup_table.get(orth, string)
else:
return lookup_table.get(string, string)
# Reimplemented to focus more on application of suffix rules and to return
# as early as possible.
def lemmatize(self, string, index, exceptions, rules):
# returns (forms, is_known: bool)
oov_forms = []
for old, new in rules:
if string.endswith(old):
form = string[: len(string) - len(old)] + new
if not form:
pass
elif form in index:
return [form], True # True = Is known (is lemma)
else:
oov_forms.append(form)
return list(set(oov_forms)), False