spaCy/spacy/lang/fr/lemmatizer/lemmatizer.py
Paul O'Leary McCann 756b66b7c0 Reduce size of language data (#4141)
* Move Turkish lemmas to a json file

Rather than a large dict in Python source, the data is now a big json
file. This includes a method for loading the json file, falling back to
a compressed file, and an update to MANIFEST.in that excludes json in
the spacy/lang directory.

This focuses on Turkish specifically because it has the most language
data in core.

* Transition all lemmatizer.py files to json

This covers all lemmatizer.py files of a significant size (>500k or so).
Small files were left alone.

None of the affected files have logic, so this was pretty
straightforward.

One unusual thing is that the lemma data for Urdu doesn't seem to be
used anywhere. That may require further investigation.

* Move large lang data to json for fr/nb/nl/sv

These are the languages that use a lemmatizer directory (rather than a
single file) and are larger than English.

For most of these languages there were many language data files, in
which case only the large ones (>500k or so) were converted to json. It
may or may not be a good idea to migrate the remaining Python files to
json in the future.

* Fix id lemmas.json

The contents of this file were originally just copied from the Python
source, but that used single quotes, so it had to be properly converted
to json first.

* Add .json.gz to gitignore

This covers the json.gz files built as part of distribution.

* Add language data gzip to build process

Currently this gzip data on every build; it works, but it should be
changed to only gzip when the source file has been updated.

* Remove Danish lemmatizer.py

Missed this when I added the json.

* Update to match latest explosion/srsly#9

The way gzipped json is loaded/saved in srsly changed a bit.

* Only compress language data if necessary

If a .json.gz file exists and is newer than the corresponding json file,
it's not recompressed.

* Move en/el language data to json

This only affected files >500kb, which was nouns for both languages and
the generic lookup table for English.

* Remove empty files in Norwegian tokenizer

It's unclear why, but the Norwegian (nb) tokenizer had empty files for
adj/adv/noun/verb lemmas. This may have been a result of copying the
structure of the English lemmatizer.

This removed the files, but still creates the empty sets in the
lemmatizer. That may not actually be necessary.

* Remove dubious entries in English lookup.json

" furthest" and " skilled" - both prefixed with a space - were in the
English lookup table. That seems obviously wrong so I have removed them.

* Fix small issues with en/fr lemmatizers

The en tokenizer was including the removed _nouns.py file, so that's
removed.

The fr tokenizer is unusual in that it has a lemmatizer directory with
both __init__.py and lemmatizer.py. lemmatizer.py had not been converted
to load the json language data, so that was fixed.

* Auto-format

* Auto-format

* Update srsly pin

* Consistently use pathlib paths
2019-08-20 14:54:11 +02:00

142 lines
5.1 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from pathlib import Path
from ....symbols import POS, NOUN, VERB, ADJ, ADV, PRON, DET, AUX, PUNCT, ADP, SCONJ, CCONJ
from ....symbols import VerbForm_inf, VerbForm_none, Number_sing, Degree_pos
from ....util import load_language_data
LOOKUP = load_language_data(Path(__file__).parent / 'lookup.json')
'''
French language lemmatizer applies the default rule based lemmatization
procedure with some modifications for better French language support.
The parts of speech 'ADV', 'PRON', 'DET', 'ADP' and 'AUX' are added to use the
rule-based lemmatization. As a last resort, the lemmatizer checks in
the lookup table.
'''
class FrenchLemmatizer(object):
@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
self.lookup_table = lookup if lookup is not None else {}
def __call__(self, string, univ_pos, morphology=None):
if not self.rules:
return [self.lookup_table.get(string, string)]
if univ_pos in (NOUN, 'NOUN', 'noun'):
univ_pos = 'noun'
elif univ_pos in (VERB, 'VERB', 'verb'):
univ_pos = 'verb'
elif univ_pos in (ADJ, 'ADJ', 'adj'):
univ_pos = 'adj'
elif univ_pos in (ADP, 'ADP', 'adp'):
univ_pos = 'adp'
elif univ_pos in (ADV, 'ADV', 'adv'):
univ_pos = 'adv'
elif univ_pos in (AUX, 'AUX', 'aux'):
univ_pos = 'aux'
elif univ_pos in (CCONJ, 'CCONJ', 'cconj'):
univ_pos = 'cconj'
elif univ_pos in (DET, 'DET', 'det'):
univ_pos = 'det'
elif univ_pos in (PRON, 'PRON', 'pron'):
univ_pos = 'pron'
elif univ_pos in (PUNCT, 'PUNCT', 'punct'):
univ_pos = 'punct'
elif univ_pos in (SCONJ, 'SCONJ', 'sconj'):
univ_pos = 'sconj'
else:
return [self.lookup(string)]
# See Issue #435 for example of where this logic is requied.
if self.is_base_form(univ_pos, morphology):
return list(set([string.lower()]))
lemmas = lemmatize(string, self.index.get(univ_pos, {}),
self.exc.get(univ_pos, {}),
self.rules.get(univ_pos, []))
return lemmas
def is_base_form(self, univ_pos, morphology=None):
"""
Check whether we're dealing with an uninflected paradigm, so we can
avoid lemmatization entirely.
"""
morphology = {} if morphology is None else morphology
others = [key for key in morphology
if key not in (POS, 'Number', 'POS', 'VerbForm', 'Tense')]
if univ_pos == 'noun' and morphology.get('Number') == 'sing':
return True
elif univ_pos == 'verb' and morphology.get('VerbForm') == 'inf':
return True
# This maps 'VBP' to base form -- probably just need 'IS_BASE'
# morphology
elif univ_pos == 'verb' and (morphology.get('VerbForm') == 'fin' and
morphology.get('Tense') == 'pres' and
morphology.get('Number') is None and
not others):
return True
elif univ_pos == 'adj' and morphology.get('Degree') == 'pos':
return True
elif VerbForm_inf in morphology:
return True
elif VerbForm_none in morphology:
return True
elif Number_sing in morphology:
return True
elif Degree_pos in morphology:
return True
else:
return False
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 punct(self, string, morphology=None):
return self(string, 'punct', morphology)
def lookup(self, string):
if string in self.lookup_table:
return self.lookup_table[string][0]
return string
def lemmatize(string, index, exceptions, rules):
string = string.lower()
forms = []
if (string in index):
forms.append(string)
return forms
forms.extend(exceptions.get(string, []))
oov_forms = []
if not 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 or not form.isalpha():
forms.append(form)
else:
oov_forms.append(form)
if not forms:
forms.extend(oov_forms)
if not forms and string in LOOKUP.keys():
forms.append(LOOKUP[string][0])
if not forms:
forms.append(string)
return list(set(forms))