mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-11 20:28:20 +03:00
108 lines
3.6 KiB
Python
108 lines
3.6 KiB
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
from ...lemmatizer import Lemmatizer
|
|
from ...parts_of_speech import NAMES
|
|
from ...errors import Errors
|
|
|
|
|
|
class PolishLemmatizer(Lemmatizer):
|
|
# This lemmatizer implements lookup lemmatization based on
|
|
# the Morfeusz dictionary (morfeusz.sgjp.pl/en) by Institute of Computer Science PAS
|
|
# It utilizes some prefix based improvements for
|
|
# verb and adjectives lemmatization, as well as case-sensitive
|
|
# lemmatization for nouns
|
|
def __init__(self, lookups, *args, **kwargs):
|
|
# this lemmatizer is lookup based, so it does not require an index, exceptionlist, or rules
|
|
super().__init__(lookups)
|
|
self.lemma_lookups = {}
|
|
for tag in [
|
|
"ADJ",
|
|
"ADP",
|
|
"ADV",
|
|
"AUX",
|
|
"NOUN",
|
|
"NUM",
|
|
"PART",
|
|
"PRON",
|
|
"VERB",
|
|
"X",
|
|
]:
|
|
self.lemma_lookups[tag] = self.lookups.get_table(
|
|
"lemma_lookup_" + tag.lower(), {}
|
|
)
|
|
self.lemma_lookups["DET"] = self.lemma_lookups["X"]
|
|
self.lemma_lookups["PROPN"] = self.lemma_lookups["NOUN"]
|
|
|
|
def __call__(self, string, univ_pos, morphology=None):
|
|
if isinstance(univ_pos, int):
|
|
univ_pos = NAMES.get(univ_pos, "X")
|
|
univ_pos = univ_pos.upper()
|
|
|
|
if univ_pos == "NOUN":
|
|
return self.lemmatize_noun(string, morphology)
|
|
|
|
if univ_pos != "PROPN":
|
|
string = string.lower()
|
|
|
|
if univ_pos == "ADJ":
|
|
return self.lemmatize_adj(string, morphology)
|
|
elif univ_pos == "VERB":
|
|
return self.lemmatize_verb(string, morphology)
|
|
|
|
lemma_dict = self.lemma_lookups.get(univ_pos, {})
|
|
return [lemma_dict.get(string, string.lower())]
|
|
|
|
def lemmatize_adj(self, string, morphology):
|
|
# this method utilizes different procedures for adjectives
|
|
# with 'nie' and 'naj' prefixes
|
|
lemma_dict = self.lemma_lookups["ADJ"]
|
|
|
|
if string[:3] == "nie":
|
|
search_string = string[3:]
|
|
if search_string[:3] == "naj":
|
|
naj_search_string = search_string[3:]
|
|
if naj_search_string in lemma_dict:
|
|
return [lemma_dict[naj_search_string]]
|
|
if search_string in lemma_dict:
|
|
return [lemma_dict[search_string]]
|
|
|
|
if string[:3] == "naj":
|
|
naj_search_string = string[3:]
|
|
if naj_search_string in lemma_dict:
|
|
return [lemma_dict[naj_search_string]]
|
|
|
|
return [lemma_dict.get(string, string)]
|
|
|
|
def lemmatize_verb(self, string, morphology):
|
|
# this method utilizes a different procedure for verbs
|
|
# with 'nie' prefix
|
|
lemma_dict = self.lemma_lookups["VERB"]
|
|
|
|
if string[:3] == "nie":
|
|
search_string = string[3:]
|
|
if search_string in lemma_dict:
|
|
return [lemma_dict[search_string]]
|
|
|
|
return [lemma_dict.get(string, string)]
|
|
|
|
def lemmatize_noun(self, string, morphology):
|
|
# this method is case-sensitive, in order to work
|
|
# for incorrectly tagged proper names
|
|
lemma_dict = self.lemma_lookups["NOUN"]
|
|
|
|
if string != string.lower():
|
|
if string.lower() in lemma_dict:
|
|
return [lemma_dict[string.lower()]]
|
|
elif string in lemma_dict:
|
|
return [lemma_dict[string]]
|
|
return [string.lower()]
|
|
|
|
return [lemma_dict.get(string, string)]
|
|
|
|
def lookup(self, string, orth=None):
|
|
return string.lower()
|
|
|
|
def lemmatize(self, string, index, exceptions, rules):
|
|
raise NotImplementedError
|