spaCy/spacy/tests/lang/nl/test_lemmatizer.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

144 lines
3.7 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
import pytest
# Calling the Lemmatizer directly
# Imitates behavior of:
# Tagger.set_annotations()
# -> vocab.morphology.assign_tag_id()
# -> vocab.morphology.assign_tag_id()
# -> Token.tag.__set__
# -> vocab.morphology.assign_tag(...)
# -> ... -> Morphology.assign_tag(...)
# -> self.lemmatize(analysis.tag.pos, token.lex.orth,
noun_irreg_lemmatization_cases = [
("volkeren", "volk"),
("vaatje", "vat"),
("verboden", "verbod"),
("ijsje", "ijsje"),
("slagen", "slag"),
("verdragen", "verdrag"),
("verloven", "verlof"),
("gebeden", "gebed"),
("gaten", "gat"),
("staven", "staf"),
("aquariums", "aquarium"),
("podia", "podium"),
("holen", "hol"),
("lammeren", "lam"),
("bevelen", "bevel"),
("wegen", "weg"),
("moeilijkheden", "moeilijkheid"),
("aanwezigheden", "aanwezigheid"),
("goden", "god"),
("loten", "lot"),
("kaarsen", "kaars"),
("leden", "lid"),
("glaasje", "glas"),
("eieren", "ei"),
("vatten", "vat"),
("kalveren", "kalf"),
("padden", "pad"),
("smeden", "smid"),
("genen", "gen"),
("beenderen", "been"),
]
verb_irreg_lemmatization_cases = [
("liep", "lopen"),
("hief", "heffen"),
("begon", "beginnen"),
("sla", "slaan"),
("aangekomen", "aankomen"),
("sproot", "spruiten"),
("waart", "zijn"),
("snoof", "snuiven"),
("spoot", "spuiten"),
("ontbeet", "ontbijten"),
("gehouwen", "houwen"),
("afgewassen", "afwassen"),
("deed", "doen"),
("schoven", "schuiven"),
("gelogen", "liegen"),
("woog", "wegen"),
("gebraden", "braden"),
("smolten", "smelten"),
("riep", "roepen"),
("aangedaan", "aandoen"),
("vermeden", "vermijden"),
("stootten", "stoten"),
("ging", "gaan"),
("geschoren", "scheren"),
("gesponnen", "spinnen"),
("reden", "rijden"),
("zochten", "zoeken"),
("leed", "lijden"),
("verzonnen", "verzinnen"),
]
@pytest.mark.parametrize("text,lemma", noun_irreg_lemmatization_cases)
def test_nl_lemmatizer_noun_lemmas_irreg(nl_lemmatizer, text, lemma):
pos = "noun"
lemmas_pred = nl_lemmatizer(text, pos)
assert lemma == sorted(lemmas_pred)[0]
@pytest.mark.parametrize("text,lemma", verb_irreg_lemmatization_cases)
def test_nl_lemmatizer_verb_lemmas_irreg(nl_lemmatizer, text, lemma):
pos = "verb"
lemmas_pred = nl_lemmatizer(text, pos)
assert lemma == sorted(lemmas_pred)[0]
@pytest.mark.skip
@pytest.mark.parametrize("text,lemma", [])
def test_nl_lemmatizer_verb_lemmas_reg(nl_lemmatizer, text, lemma):
# TODO: add test
pass
@pytest.mark.skip
@pytest.mark.parametrize("text,lemma", [])
def test_nl_lemmatizer_adjective_lemmas(nl_lemmatizer, text, lemma):
# TODO: add test
pass
@pytest.mark.skip
@pytest.mark.parametrize("text,lemma", [])
def test_nl_lemmatizer_determiner_lemmas(nl_lemmatizer, text, lemma):
# TODO: add test
pass
@pytest.mark.skip
@pytest.mark.parametrize("text,lemma", [])
def test_nl_lemmatizer_adverb_lemmas(nl_lemmatizer, text, lemma):
# TODO: add test
pass
@pytest.mark.parametrize("text,lemma", [])
def test_nl_lemmatizer_pronoun_lemmas(nl_lemmatizer, text, lemma):
# TODO: add test
pass
# Using the lemma lookup table only
@pytest.mark.parametrize("text,lemma", noun_irreg_lemmatization_cases)
def test_nl_lemmatizer_lookup_noun(nl_lemmatizer, text, lemma):
lemma_pred = nl_lemmatizer.lookup(None, text)
assert lemma_pred in (lemma, text)
@pytest.mark.parametrize("text,lemma", verb_irreg_lemmatization_cases)
def test_nl_lemmatizer_lookup_verb(nl_lemmatizer, text, lemma):
lemma_pred = nl_lemmatizer.lookup(None, text)
assert lemma_pred in (lemma, text)