Catalan Language Support (#2940)

* Catalan language Support

* Ddding Catalan to documentation

.github/contributors/mpuig.md

@@ -0,0 +1,106 @@
+# spaCy contributor agreement
+
+This spaCy Contributor Agreement (**"SCA"**) is based on the
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+
+## Contributor Details
+
+| Field                          | Entry                |
+|------------------------------- | -------------------- |
+| Name                           | Marc Puig            |
+| Company name (if applicable)   |                      |
+| Title or role (if applicable)  |                      |
+| Date                           | 2018-11-17           |
+| GitHub username                | mpuig                |
+| Website (optional)             |                      |

spacy/lang/ca/__init__.py

@@ -0,0 +1,64 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
+from .stop_words import STOP_WORDS
+from .lex_attrs import LEX_ATTRS
+
+# uncomment if files are available
+# from .norm_exceptions import NORM_EXCEPTIONS
+# from .tag_map import TAG_MAP
+# from .morph_rules import MORPH_RULES
+
+# uncomment if lookup-based lemmatizer is available
+from .lemmatizer import LOOKUP
+
+from ..tokenizer_exceptions import BASE_EXCEPTIONS
+from ..norm_exceptions import BASE_NORMS
+from ...language import Language
+from ...attrs import LANG, NORM
+from ...util import update_exc, add_lookups
+
+# Create a Language subclass
+# Documentation: https://spacy.io/docs/usage/adding-languages
+
+# This file should be placed in spacy/lang/ca (ISO code of language).
+# Before submitting a pull request, make sure the remove all comments from the
+# language data files, and run at least the basic tokenizer tests. Simply add the
+# language ID to the list of languages in spacy/tests/conftest.py to include it
+# in the basic tokenizer sanity tests. You can optionally add a fixture for the
+# language's tokenizer and add more specific tests. For more info, see the
+# tests documentation: https://github.com/explosion/spaCy/tree/master/spacy/tests
+
+
+class CatalanDefaults(Language.Defaults):
+    lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
+    lex_attr_getters[LANG] = lambda text: 'ca' # ISO code
+    # add more norm exception dictionaries here
+    lex_attr_getters[NORM] = add_lookups(Language.Defaults.lex_attr_getters[NORM], BASE_NORMS)
+
+    # overwrite functions for lexical attributes
+    lex_attr_getters.update(LEX_ATTRS)
+
+    # add custom tokenizer exceptions to base exceptions
+    tokenizer_exceptions = update_exc(BASE_EXCEPTIONS, TOKENIZER_EXCEPTIONS)
+
+    # add stop words
+    stop_words = STOP_WORDS
+
+    # if available: add tag map
+    # tag_map = dict(TAG_MAP)
+
+    # if available: add morph rules
+    # morph_rules = dict(MORPH_RULES)
+
+    lemma_lookup = LOOKUP
+
+
+class Catalan(Language):
+    lang = 'ca' # ISO code
+    Defaults = CatalanDefaults # set Defaults to custom language defaults
+
+
+# set default export – this allows the language class to be lazy-loaded
+__all__ = ['Catalan']

spacy/lang/ca/examples.py

@@ -0,0 +1,22 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+
+"""
+Example sentences to test spaCy and its language models.
+
+>>> from spacy.lang.es.examples import sentences
+>>> docs = nlp.pipe(sentences)
+"""
+
+
+sentences = [
+    "Apple està buscant comprar una startup del Regne Unit per mil milions de dòlars",
+    "Els cotxes autònoms deleguen la responsabilitat de l'assegurança als seus fabricants",
+    "San Francisco analitza prohibir els robots de repartiment",
+    "Londres és una gran ciutat del Regne Unit",
+    "El gat menja peix",
+    "Veig a l'home amb el telescopi",
+    "L'Aranya menja mosques",
+    "El pingüí incuba en el seu niu",
+]

spacy/lang/ca/lex_attrs.py

@@ -0,0 +1,43 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+# import the symbols for the attrs you want to overwrite
+from ...attrs import LIKE_NUM
+
+
+# Overwriting functions for lexical attributes
+# Documentation: https://localhost:1234/docs/usage/adding-languages#lex-attrs
+# Most of these functions, like is_lower or like_url should be language-
+# independent. Others, like like_num (which includes both digits and number
+# words), requires customisation.
+
+
+# Example: check if token resembles a number
+
+_num_words = ['zero', 'un', 'dos', 'tres', 'quatre', 'cinc', 'sis', 'set',
+              'vuit', 'nou', 'deu', 'onze', 'dotze', 'tretze', 'catorze',
+              'quinze', 'setze', 'disset', 'divuit', 'dinou', 'vint',
+              'trenta', 'quaranta', 'cinquanta', 'seixanta', 'setanta', 'vuitanta', 'noranta',
+              'cent', 'mil', 'milió', 'bilió', 'trilió', 'quatrilió',
+              'gazilió', 'bazilió']
+
+
+def like_num(text):
+    text = text.replace(',', '').replace('.', '')
+    if text.isdigit():
+        return True
+    if text.count('/') == 1:
+        num, denom = text.split('/')
+        if num.isdigit() and denom.isdigit():
+            return True
+    if text in _num_words:
+        return True
+    return False
+
+
+# Create dictionary of functions to overwrite. The default lex_attr_getters are
+# updated with this one, so only the functions defined here are overwritten.
+
+LEX_ATTRS = {
+    LIKE_NUM: like_num
+}

spacy/lang/ca/stop_words.py

@@ -0,0 +1,56 @@
+# encoding: utf8
+from __future__ import unicode_literals
+
+
+# Stop words
+
+STOP_WORDS = set("""
+a abans ací ah així això al aleshores algun alguna algunes alguns alhora allà allí allò
+als altra altre altres amb ambdues ambdós anar ans apa aquell aquella aquelles aquells
+aquest aquesta aquestes aquests aquí
+
+baix bastant bé
+
+cada cadascuna cadascunes cadascuns cadascú com consegueixo conseguim conseguir
+consigueix consigueixen consigueixes contra
+
+d'un d'una d'unes d'uns dalt de del dels des des de després dins dintre donat doncs durant
+
+e eh el elles ells els em en encara ens entre era erem eren eres es esta estan estat
+estava estaven estem esteu estic està estàvem estàveu et etc ets érem éreu és éssent
+
+fa faig fan fas fem fer feu fi fins fora
+
+gairebé
+
+ha han has haver havia he hem heu hi ho
+
+i igual iguals inclòs
+
+ja jo
+
+l'hi la les li li'n llarg llavors
+
+m'he ma mal malgrat mateix mateixa mateixes mateixos me mentre meu meus meva
+meves mode molt molta moltes molts mon mons més
+
+n'he n'hi ne ni no nogensmenys només nosaltres nostra nostre nostres
+
+o oh oi on
+
+pas pel pels per per que perquè però poc poca pocs podem poden poder
+podeu poques potser primer propi puc
+
+qual quals quan quant que quelcom qui quin quina quines quins què
+
+s'ha s'han sa sabem saben saber sabeu sap saps semblant semblants sense ser ses
+seu seus seva seves si sobre sobretot soc solament sols som son sons sota sou sóc són
+
+t'ha t'han t'he ta tal també tampoc tan tant tanta tantes te tene tenim tenir teniu
+teu teus teva teves tinc ton tons tot tota totes tots
+
+un una unes uns us últim ús
+
+va vaig vam van vas veu vosaltres vostra vostre vostres
+
+""".split())

spacy/lang/ca/tag_map.py

@@ -0,0 +1,36 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+from ..symbols import POS, ADV, NOUN, ADP, PRON, SCONJ, PROPN, DET, SYM, INTJ
+from ..symbols import PUNCT, NUM, AUX, X, CONJ, ADJ, VERB, PART, SPACE, CCONJ
+
+
+# Add a tag map
+# Documentation: https://spacy.io/docs/usage/adding-languages#tag-map
+# Universal Dependencies: http://universaldependencies.org/u/pos/all.html
+# The keys of the tag map should be strings in your tag set. The dictionary must
+# have an entry POS whose value is one of the Universal Dependencies tags.
+# Optionally, you can also include morphological features or other attributes.
+
+
+TAG_MAP = {
+    "ADV":      {POS: ADV},
+    "NOUN":     {POS: NOUN},
+    "ADP":      {POS: ADP},
+    "PRON":     {POS: PRON},
+    "SCONJ":    {POS: SCONJ},
+    "PROPN":    {POS: PROPN},
+    "DET":      {POS: DET},
+    "SYM":      {POS: SYM},
+    "INTJ":     {POS: INTJ},
+    "PUNCT":    {POS: PUNCT},
+    "NUM":      {POS: NUM},
+    "AUX":      {POS: AUX},
+    "X":        {POS: X},
+    "CONJ":     {POS: CONJ},
+    "CCONJ":    {POS: CCONJ},
+    "ADJ":      {POS: ADJ},
+    "VERB":     {POS: VERB},
+    "PART":     {POS: PART},
+    "SP":     	{POS: SPACE}
+}

spacy/lang/ca/tokenizer_exceptions.py

@@ -0,0 +1,51 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+# import symbols – if you need to use more, add them here
+from ...symbols import ORTH, LEMMA, TAG, NORM, ADP, DET
+
+
+_exc = {}
+
+for exc_data in [
+    {ORTH: "aprox.", LEMMA: "aproximadament"},
+    {ORTH: "pàg.", LEMMA: "pàgina"},
+    {ORTH: "p.ex.", LEMMA: "per exemple"},
+    {ORTH: "gen.", LEMMA: "gener"},
+    {ORTH: "feb.", LEMMA: "febrer"},
+    {ORTH: "abr.", LEMMA: "abril"},
+    {ORTH: "jul.", LEMMA: "juliol"},
+    {ORTH: "set.", LEMMA: "setembre"},
+    {ORTH: "oct.", LEMMA: "octubre"},
+    {ORTH: "nov.", LEMMA: "novembre"},
+    {ORTH: "dec.", LEMMA: "desembre"},
+    {ORTH: "Dr.", LEMMA: "doctor"},
+    {ORTH: "Sr.", LEMMA: "senyor"},
+    {ORTH: "Sra.", LEMMA: "senyora"},
+    {ORTH: "Srta.", LEMMA: "senyoreta"},
+    {ORTH: "núm", LEMMA: "número"},
+    {ORTH: "St.", LEMMA: "sant"},
+    {ORTH: "Sta.", LEMMA: "santa"}]:
+    _exc[exc_data[ORTH]] = [exc_data]
+
+# Times
+
+_exc["12m."] = [
+    {ORTH: "12"},
+    {ORTH: "m.", LEMMA: "p.m."}]
+
+
+for h in range(1, 12 + 1):
+    for period in ["a.m.", "am"]:
+        _exc["%d%s" % (h, period)] = [
+            {ORTH: "%d" % h},
+            {ORTH: period, LEMMA: "a.m."}]
+    for period in ["p.m.", "pm"]:
+        _exc["%d%s" % (h, period)] = [
+            {ORTH: "%d" % h},
+            {ORTH: period, LEMMA: "p.m."}]
+
+# To keep things clean and readable, it's recommended to only declare the
+# TOKENIZER_EXCEPTIONS at the bottom:
+
+TOKENIZER_EXCEPTIONS = _exc

spacy/tests/conftest.py

@@ -14,7 +14,7 @@ from .. import util
 # These languages are used for generic tokenizer tests – only add a language
 # here if it's using spaCy's tokenizer (not a different library)
 # TODO: re-implement generic tokenizer tests
-_languages = ['bn', 'da', 'de', 'el', 'en', 'es', 'fi', 'fr', 'ga', 'he', 'hu', 'id',
+_languages = ['bn', 'ca', 'da', 'de', 'el', 'en', 'es', 'fi', 'fr', 'ga', 'he', 'hu', 'id',
               'it', 'nb', 'nl', 'pl', 'pt', 'ro', 'ru', 'sv', 'tr', 'ar', 'ut', 'tt',
               'xx']
 
@@ -175,6 +175,10 @@ def ru_tokenizer():
     pymorphy = pytest.importorskip('pymorphy2')
     return util.get_lang_class('ru').Defaults.create_tokenizer()
 
+@pytest.fixture(scope='session')
+def ca_tokenizer():
+    return util.get_lang_class('ca').Defaults.create_tokenizer()
+
 
 @pytest.fixture
 def stringstore():

spacy/tests/lang/ca/test_exception.py

@@ -0,0 +1,23 @@
+# coding: utf-8
+
+from __future__ import unicode_literals
+
+import pytest
+
+
+@pytest.mark.parametrize('text,lemma', [("aprox.", "aproximadament"),
+                                        ("pàg.", "pàgina"),
+                                        ("p.ex.", "per exemple")
+                                        ])
+def test_ca_tokenizer_handles_abbr(ca_tokenizer, text, lemma):
+    tokens = ca_tokenizer(text)
+    assert len(tokens) == 1
+    assert tokens[0].lemma_ == lemma
+
+
+def test_ca_tokenizer_handles_exc_in_text(ca_tokenizer):
+    text = "La Núria i el Pere han vingut aprox. a les 7 de la tarda."
+    tokens = ca_tokenizer(text)
+    assert len(tokens) == 15
+    assert tokens[7].text == "aprox."
+    assert tokens[7].lemma_ == "aproximadament"

spacy/tests/lang/ca/test_text.py

@@ -0,0 +1,42 @@
+# coding: utf-8
+
+"""Test that longer and mixed texts are tokenized correctly."""
+
+
+from __future__ import unicode_literals
+
+import pytest
+
+
+def test_ca_tokenizer_handles_long_text(ca_tokenizer):
+    text = """Una taula amb grans gerres de begudes i palles de coloraines com a reclam. Una carta
+    cridanera amb ofertes de tapes, paelles i sangria. Un cambrer amb un somriure que convida a
+    seure. La ubicació perfecta: el bell mig de la Rambla. Però és la una del migdia d’un dimecres
+    de tardor i no hi ha ningú assegut a la terrassa del local. El dia és rúfol, però no fa fred i
+    a la majoria de terrasses de la Rambla hi ha poca gent. La immensa majoria dels clients -tret
+    d’alguna excepció com al restaurant Núria- són turistes. I la immensa majoria tenen entre mans
+    una gerra de cervesa. Ens asseiem -fotògraf i periodista- en una terrassa buida."""
+
+    tokens = ca_tokenizer(text)
+    assert len(tokens) == 136
+
+
+@pytest.mark.parametrize('text,length', [
+    ("Perquè va anar-hi?", 6),
+    ("“Ah no?”", 5),
+    ("""Sí! "Anem", va contestar el Joan Carles""", 11),
+    ("Van córrer aprox. 10km", 5),
+    ("Llavors perqué...", 3)])
+def test_ca_tokenizer_handles_cnts(ca_tokenizer, text, length):
+    tokens = ca_tokenizer(text)
+    assert len(tokens) == length
+
+
+@pytest.mark.parametrize('text,match', [
+    ('10', True), ('1', True), ('10,000', True), ('10,00', True),
+    ('999.0', True), ('un', True), ('dos', True), ('bilió', True),
+    ('gos', False), (',', False), ('1/2', True)])
+def test_ca_lex_attrs_like_number(ca_tokenizer, text, match):
+    tokens = ca_tokenizer(text)
+    assert len(tokens) == 1
+    assert tokens[0].like_num == match

website/models/_data.json

@@ -121,6 +121,7 @@
         "zh": "Chinese",
         "ja": "Japanese",
         "vi": "Vietnamese",
+        "ca": "Catalan",
         "xx": "Multi-language"
     },