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1eed101be9
Restructure Polish lemmatizer not to depend on lookups data in `__init__` since the lemmatizer is initialized before the lookups data is loaded from a saved model. The lookups tables are accessed first in `__call__` instead once the data is available.
82 lines
3.0 KiB
Python
82 lines
3.0 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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from ...lemmatizer import Lemmatizer
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from ...parts_of_speech import NAMES
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class PolishLemmatizer(Lemmatizer):
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# This lemmatizer implements lookup lemmatization based on the Morfeusz
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# dictionary (morfeusz.sgjp.pl/en) by Institute of Computer Science PAS.
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# It utilizes some prefix based improvements for verb and adjectives
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# lemmatization, as well as case-sensitive lemmatization for nouns.
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def __call__(self, string, univ_pos, morphology=None):
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if isinstance(univ_pos, int):
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univ_pos = NAMES.get(univ_pos, "X")
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univ_pos = univ_pos.upper()
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lookup_pos = univ_pos.lower()
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if univ_pos == "PROPN":
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lookup_pos = "noun"
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lookup_table = self.lookups.get_table("lemma_lookup_" + lookup_pos, {})
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if univ_pos == "NOUN":
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return self.lemmatize_noun(string, morphology, lookup_table)
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if univ_pos != "PROPN":
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string = string.lower()
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if univ_pos == "ADJ":
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return self.lemmatize_adj(string, morphology, lookup_table)
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elif univ_pos == "VERB":
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return self.lemmatize_verb(string, morphology, lookup_table)
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return [lookup_table.get(string, string.lower())]
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def lemmatize_adj(self, string, morphology, lookup_table):
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# this method utilizes different procedures for adjectives
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# with 'nie' and 'naj' prefixes
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if string[:3] == "nie":
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search_string = string[3:]
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if search_string[:3] == "naj":
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naj_search_string = search_string[3:]
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if naj_search_string in lookup_table:
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return [lookup_table[naj_search_string]]
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if search_string in lookup_table:
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return [lookup_table[search_string]]
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if string[:3] == "naj":
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naj_search_string = string[3:]
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if naj_search_string in lookup_table:
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return [lookup_table[naj_search_string]]
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return [lookup_table.get(string, string)]
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def lemmatize_verb(self, string, morphology, lookup_table):
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# this method utilizes a different procedure for verbs
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# with 'nie' prefix
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if string[:3] == "nie":
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search_string = string[3:]
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if search_string in lookup_table:
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return [lookup_table[search_string]]
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return [lookup_table.get(string, string)]
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def lemmatize_noun(self, string, morphology, lookup_table):
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# this method is case-sensitive, in order to work
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# for incorrectly tagged proper names
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if string != string.lower():
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if string.lower() in lookup_table:
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return [lookup_table[string.lower()]]
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elif string in lookup_table:
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return [lookup_table[string]]
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return [string.lower()]
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return [lookup_table.get(string, string)]
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def lookup(self, string, orth=None):
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return string.lower()
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def lemmatize(self, string, index, exceptions, rules):
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raise NotImplementedError
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