spaCy/spacy/lang/nl/lemmatizer/__init__.py
Paul O'Leary McCann 7d8df69158 Bloom-filter backed Lookup Tables (#4268)
* Improve load_language_data helper

* WIP: Add Lookups implementation

* Start moving lemma data over to JSON

* WIP: move data over for more languages

* Convert more languages

* Fix lemmatizer fixtures in tests

* Finish conversion

* Auto-format JSON files

* Fix test for now

* Make sure tables are stored on instance

* Update docstrings

* Update docstrings and errors

* Update test

* Add Lookups.__len__

* Add serialization methods

* Add Lookups.remove_table

* Use msgpack for serialization to disk

* Fix file exists check

* Try using OrderedDict for everything

* Update .flake8 [ci skip]

* Try fixing serialization

* Update test_lookups.py

* Update test_serialize_vocab_strings.py

* Lookups / Tables now work

This implements the stubs in the Lookups/Table classes. Currently this
is in Cython but with no type declarations, so that could be improved.

* Add lookups to setup.py

* Actually add lookups pyx

The previous commit added the old py file...

* Lookups work-in-progress

* Move from pyx back to py

* Add string based lookups, fix serialization

* Update tests, language/lemmatizer to work with string lookups

There are some outstanding issues here:

- a pickling-related test fails due to the bloom filter
- some custom lemmatizers (fr/nl at least) have issues

More generally, there's a question of how to deal with the case where
you have a string but want to use the lookup table. Currently the table
allows access by string or id, but that's getting pretty awkward.

* Change lemmatizer lookup method to pass (orth, string)

* Fix token lookup

* Fix French lookup

* Fix lt lemmatizer test

* Fix Dutch lemmatizer

* Fix lemmatizer lookup test

This was using a normal dict instead of a Table, so checks for the
string instead of an integer key failed.

* Make uk/nl/ru lemmatizer lookup methods consistent

The mentioned tokenizers all have their own implementation of the
`lookup` method, which accesses a `Lookups` table. The way that was
called in `token.pyx` was changed so this should be updated to have the
same arguments as `lookup` in `lemmatizer.py` (specificially (orth/id,
string)).

Prior to this change tests weren't failing, but there would probably be
issues with normal use of a model. More tests should proably be added.

Additionally, the language-specific `lookup` implementations seem like
they might not be needed, since they handle things like lower-casing
that aren't actually language specific.

* Make recently added Greek method compatible

* Remove redundant class/method

Leftovers from a merge not cleaned up adequately.
2019-09-12 17:26:11 +02:00

150 lines
4.9 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from ....symbols import 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_string(univ_pos, {})
# string is already lemma
if string in lemma_index:
return [string]
exceptions = self.exc.get_string(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(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_string(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, orth, string):
string = string.lower()
if orth is not None:
return self.lookup_table.get(orth, string)
else:
return self.lookup_table.get_string(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