Rule-based French Lemmatizer (#2818)
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## Description
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testing, include information about the testing environment and the tests you
ran. If your test fixes a bug reported in an issue, don't forget to include the
issue number. If your PR is still a work in progress, that's totally fine – just
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Add a rule-based French Lemmatizer following the english one and the excellent PR for [greek language optimizations](https://github.com/explosion/spaCy/pull/2558) to adapt the Lemmatizer class.
### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->
- Lemma dictionary used can be found [here](http://infolingu.univ-mlv.fr/DonneesLinguistiques/Dictionnaires/telechargement.html), I used the XML version.
- Add several files containing exhaustive list of words for each part of speech
- Add some lemma rules
- Add POS that are not checked in the standard Lemmatizer, i.e PRON, DET, ADV and AUX
- Modify the Lemmatizer class to check in lookup table as a last resort if POS not mentionned
- Modify the lemmatize function to check in lookup table as a last resort
- Init files are updated so the model can support all the functionalities mentioned above
- Add words to tokenizer_exceptions_list.py in respect to regex used in tokenizer_exceptions.py
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [X] I have submitted the spaCy Contributor Agreement.
- [X] I ran the tests, and all new and existing tests passed.
- [X] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-10-13 14:38:21 +00:00
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# coding: utf8
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from __future__ import unicode_literals
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2019-08-22 12:21:32 +00:00
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from ....symbols import POS, NOUN, VERB, ADJ, ADV, PRON, DET, AUX, PUNCT, ADP
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from ....symbols import SCONJ, CCONJ
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from ....symbols import VerbForm_inf, VerbForm_none, Number_sing, Degree_pos
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class FrenchLemmatizer(object):
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"""
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French language lemmatizer applies the default rule based lemmatization
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procedure with some modifications for better French language support.
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The parts of speech 'ADV', 'PRON', 'DET', 'ADP' and 'AUX' are added to use
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the rule-based lemmatization. As a last resort, the lemmatizer checks in
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the lookup table.
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"""
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@classmethod
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def load(cls, path, index=None, exc=None, rules=None, lookup=None):
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return cls(index, exc, rules, lookup)
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def __init__(self, index=None, exceptions=None, rules=None, lookup=None):
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self.index = index
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self.exc = exceptions
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self.rules = rules
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self.lookup_table = lookup if lookup is not None else {}
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def __call__(self, string, univ_pos, morphology=None):
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if not self.rules:
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return [self.lookup_table.get(string, string)]
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if univ_pos in (NOUN, "NOUN", "noun"):
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univ_pos = "noun"
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elif univ_pos in (VERB, "VERB", "verb"):
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univ_pos = "verb"
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elif univ_pos in (ADJ, "ADJ", "adj"):
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univ_pos = "adj"
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elif univ_pos in (ADP, "ADP", "adp"):
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univ_pos = "adp"
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elif univ_pos in (ADV, "ADV", "adv"):
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univ_pos = "adv"
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elif univ_pos in (AUX, "AUX", "aux"):
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univ_pos = "aux"
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elif univ_pos in (CCONJ, "CCONJ", "cconj"):
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univ_pos = "cconj"
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elif univ_pos in (DET, "DET", "det"):
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univ_pos = "det"
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elif univ_pos in (PRON, "PRON", "pron"):
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univ_pos = "pron"
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elif univ_pos in (PUNCT, "PUNCT", "punct"):
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univ_pos = "punct"
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elif univ_pos in (SCONJ, "SCONJ", "sconj"):
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univ_pos = "sconj"
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else:
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return [self.lookup(string)]
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# See Issue #435 for example of where this logic is requied.
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if self.is_base_form(univ_pos, morphology):
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return list(set([string.lower()]))
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lemmas = lemmatize(
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string,
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self.index.get(univ_pos, {}),
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self.exc.get(univ_pos, {}),
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self.rules.get(univ_pos, []),
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self.lookup_table,
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)
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return lemmas
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def is_base_form(self, univ_pos, morphology=None):
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"""
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Check whether we're dealing with an uninflected paradigm, so we can
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avoid lemmatization entirely.
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"""
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morphology = {} if morphology is None else morphology
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others = [
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key
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for key in morphology
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if key not in (POS, "Number", "POS", "VerbForm", "Tense")
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]
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if univ_pos == "noun" and morphology.get("Number") == "sing":
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return True
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elif univ_pos == "verb" and morphology.get("VerbForm") == "inf":
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return True
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# This maps 'VBP' to base form -- probably just need 'IS_BASE'
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# morphology
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elif univ_pos == "verb" and (
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morphology.get("VerbForm") == "fin"
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and morphology.get("Tense") == "pres"
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and morphology.get("Number") is None
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and not others
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):
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return True
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elif univ_pos == "adj" and morphology.get("Degree") == "pos":
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return True
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elif VerbForm_inf in morphology:
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return True
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elif VerbForm_none in morphology:
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return True
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elif Number_sing in morphology:
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return True
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elif Degree_pos in morphology:
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return True
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else:
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return False
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def noun(self, string, morphology=None):
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return self(string, "noun", morphology)
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def verb(self, string, morphology=None):
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return self(string, "verb", morphology)
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def adj(self, string, morphology=None):
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return self(string, "adj", morphology)
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def punct(self, string, morphology=None):
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return self(string, "punct", morphology)
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def lookup(self, string):
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if string in self.lookup_table:
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return self.lookup_table[string][0]
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return string
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def lemmatize(string, index, exceptions, rules, lookup):
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string = string.lower()
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forms = []
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if string in index:
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forms.append(string)
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return forms
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forms.extend(exceptions.get(string, []))
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oov_forms = []
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if not forms:
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for old, new in rules:
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if string.endswith(old):
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form = string[: len(string) - len(old)] + new
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if not form:
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pass
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elif form in index or not form.isalpha():
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forms.append(form)
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else:
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oov_forms.append(form)
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if not forms:
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forms.extend(oov_forms)
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if not forms and string in lookup.keys():
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forms.append(lookup[string][0])
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if not forms:
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forms.append(string)
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return list(set(forms))
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