spaCy/spacy/lang/nl/lemmatizer/lemmatizer.py

131 lines
4.6 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from ....symbols import POS, NOUN, VERB, ADJ, NUM, DET, PRON, ADP, AUX, ADV
class DutchLemmatizer(object):
# 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"
}
@classmethod
def load(cls, path, index=None, exc=None, rules=None, lookup=None):
return cls(index, exc, rules, lookup)
def __init__(self, index=None, exceptions=None, rules=None, lookup=None):
self.index = index
self.exc = exceptions
self.rules = rules or {}
self.lookup_table = lookup if lookup is not None else {}
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)
lemma_index = self.index.get(univ_pos, {})
# string is already lemma
if string in lemma_index:
return [string]
exceptions = self.exc.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.lookup_table
looked_up_lemma = lookup_table.get(string)
if looked_up_lemma and looked_up_lemma in lemma_index:
return [looked_up_lemma]
forms, is_known = lemmatize(
string,
lemma_index,
exceptions,
self.rules.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):
string = string.lower()
return self.lookup_table.get(string, string)
def noun(self, string, morphology=None):
return self(string, 'noun', morphology)
def verb(self, string, morphology=None):
return self(string, 'verb', morphology)
def adj(self, string, morphology=None):
return self(string, 'adj', morphology)
def det(self, string, morphology=None):
return self(string, 'det', morphology)
def pron(self, string, morphology=None):
return self(string, 'pron', morphology)
def adp(self, string, morphology=None):
return self(string, 'adp', morphology)
def punct(self, string, morphology=None):
return self(string, 'punct', morphology)
# Reimplemented to focus more on application of suffix rules and to return
# as early as possible.
def lemmatize(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