Added alpha support for Tagalog language (#3062)

I have added alpha support for the Tagalog language from the Philippines. It is the basis for the country's national language Filipino. I have heavily based the format to the EN and ES languages.

I have provided several words in the lemmatizer lookup table, added stop words from a source, translated numeric words to its Tagalog counterpart, added some tokenizer exceptions, and kept the tag map the same as the English language.

While the alpha language passed the preliminary testing that you provided, I think it needs more data to be useful for most cases.

* Added alpha support for Tagalog language

* Edited contributor template

* Included SCA; Reverted templates

* Fixed SCA template

* Fixed changes in SCA template

.github/contributors/Brixjohn.md

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+# spaCy contributor agreement
+
+This spaCy Contributor Agreement (**"SCA"**) is based on the
+[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
+The SCA applies to any contribution that you make to any product or project
+managed by us (the **"project"**), and sets out the intellectual property rights
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+**"you"** shall mean the person or entity identified below.
+
+If you agree to be bound by these terms, fill in the information requested
+below and include the filled-in version with your first pull request, under the
+folder [`.github/contributors/`](/.github/contributors/). The name of the file
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+
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+
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+
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+
+## Contributor Details
+
+| Field                          | Entry                |
+|------------------------------- | -------------------- |
+| Name                           | Brixter John Lumabi  |
+| Company name (if applicable)   | Stratpoint           |
+| Title or role (if applicable)  | Software Developer   |
+| Date                           | 18 December 2018     |
+| GitHub username                | Brixjohn             |
+| Website (optional)             |                      |

spacy/lang/tl/__init__.py

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+# 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 ...lemmatizerlookup import Lemmatizer
+
+from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
+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
+
+def _return_tl(_):
+    return 'tl'
+
+
+# Create a Language subclass
+# Documentation: https://spacy.io/docs/usage/adding-languages
+
+# This file should be placed in spacy/lang/xx (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 TagalogDefaults(Language.Defaults):
+    lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
+    lex_attr_getters[LANG] = _return_tl # 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)
+
+    # if available: add lookup lemmatizer
+    # @classmethod
+    # def create_lemmatizer(cls, nlp=None):
+    #     return Lemmatizer(LOOKUP)
+
+
+class Tagalog(Language):
+    lang = 'tl' # ISO code
+    Defaults = TagalogDefaults # set Defaults to custom language defaults
+
+
+# set default export – this allows the language class to be lazy-loaded
+__all__ = ['Tagalog']

spacy/lang/tl/lemmatizer.py

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+# coding: utf8
+from __future__ import unicode_literals
+
+
+# Adding a lemmatizer lookup table
+# Documentation: https://spacy.io/docs/usage/adding-languages#lemmatizer
+# Entries should be added in the following format:
+
+
+LOOKUP = {
+    "kaugnayan": "ugnay",
+    "sangkatauhan": "tao",
+    "kanayunan": "nayon",
+    "pandaigdigan": "daigdig",
+    "kasaysayan": "saysay",
+    "kabayanihan": "bayani",
+    "karuwagan": "duwag"
+}

spacy/lang/tl/lex_attrs.py

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+# 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 = ['sero', 'isa', 'dalawa', 'tatlo', 'apat', 'lima', 'anim', 'pito',
+              'walo', 'siyam', 'sampu', 'labing-isa', 'labindalawa', 'labintatlo', 'labing-apat',
+              'labinlima', 'labing-anim', 'labimpito', 'labing-walo', 'labinsiyam', 'dalawampu',
+              'tatlumpu', 'apatnapu', 'limampu', 'animnapu', 'pitumpu', 'walumpu', 'siyamnapu',
+              'daan', 'libo', 'milyon', 'bilyon', 'trilyon', 'quadrilyon',
+              'gajilyon', 'bazilyon']
+
+
+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/tl/stop_words.py

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+# encoding: utf8
+from __future__ import unicode_literals
+
+
+# Add stop words
+# Documentation: https://spacy.io/docs/usage/adding-languages#stop-words
+# To improve readability, words should be ordered alphabetically and separated
+# by spaces and newlines. When adding stop words from an online source, always
+# include the link in a comment. Make sure to proofread and double-check the
+# words – lists available online are often known to contain mistakes.
+
+# data from https://github.com/stopwords-iso/stopwords-tl/blob/master/stopwords-tl.txt
+
+STOP_WORDS = set("""
+    akin
+    aking
+    ako
+    alin
+    am
+    amin
+    aming
+    ang
+    ano
+    anumang
+    apat
+    at
+    atin
+    ating
+    ay
+    bababa
+    bago
+    bakit
+    bawat
+    bilang
+    dahil
+    dalawa
+    dapat
+    din
+    dito
+    doon
+    gagawin
+    gayunman
+    ginagawa
+    ginawa
+    ginawang
+    gumawa
+    gusto
+    habang
+    hanggang
+    hindi
+    huwag
+    iba
+    ibaba
+    ibabaw
+    ibig
+    ikaw
+    ilagay
+    ilalim
+    ilan
+    inyong
+    isa
+    isang
+    itaas
+    ito
+    iyo
+    iyon
+    iyong
+    ka
+    kahit
+    kailangan
+    kailanman
+    kami
+    kanila
+    kanilang
+    kanino
+    kanya
+    kanyang
+    kapag
+    kapwa
+    karamihan
+    katiyakan
+    katulad
+    kaya
+    kaysa
+    ko
+    kong
+    kulang
+    kumuha
+    kung
+    laban
+    lahat
+    lamang
+    likod
+    lima
+    maaari
+    maaaring
+    maging
+    mahusay
+    makita
+    marami
+    marapat
+    masyado
+    may
+    mayroon
+    mga
+    minsan
+    mismo
+    mula
+    muli
+    na
+    nabanggit
+    naging
+    nagkaroon
+    nais
+    nakita
+    namin
+    napaka
+    narito
+    nasaan
+    ng
+    ngayon
+    ni
+    nila
+    nilang
+    nito
+    niya
+    niyang
+    noon
+    o
+    pa
+    paano
+    pababa
+    paggawa
+    pagitan
+    pagkakaroon
+    pagkatapos
+    palabas
+    pamamagitan
+    panahon
+    pangalawa
+    para
+    paraan
+    pareho
+    pataas
+    pero
+    pumunta
+    pumupunta
+    sa
+    saan
+    sabi
+    sabihin
+    sarili
+    sila
+    sino
+    siya
+    tatlo
+    tayo
+    tulad
+    tungkol
+    una
+    walang
+""".split())

spacy/lang/tl/tag_map.py

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+# 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/tl/tokenizer_exceptions.py

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+# 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
+
+
+# Add tokenizer exceptions
+# Documentation: https://spacy.io/docs/usage/adding-languages#tokenizer-exceptions
+# Feel free to use custom logic to generate repetitive exceptions more efficiently.
+# If an exception is split into more than one token, the ORTH values combined always
+# need to match the original string.
+
+# Exceptions should be added in the following format:
+
+_exc = {
+    "tayo'y": [
+        {ORTH: "tayo", LEMMA: "tayo"},
+        {ORTH: "'y", LEMMA: "ay"}],
+    "isa'y": [
+        {ORTH: "isa", LEMMA: "isa"},
+        {ORTH: "'y", LEMMA: "ay"}],
+    "baya'y": [
+        {ORTH: "baya", LEMMA: "bayan"},
+        {ORTH: "'y", LEMMA: "ay"}],
+    "sa'yo": [
+        {ORTH: "sa", LEMMA: "sa"},
+        {ORTH: "'yo", LEMMA: "iyo"}],
+    "ano'ng": [
+        {ORTH: "ano", LEMMA: "ano"},
+        {ORTH: "'ng", LEMMA: "ang"}],
+    "siya'y": [
+        {ORTH: "siya", LEMMA: "siya"},
+        {ORTH: "'y", LEMMA: "ay"}],
+    "nawa'y": [
+        {ORTH: "nawa", LEMMA: "nawa"},
+        {ORTH: "'y", LEMMA: "ay"}],
+    "papa'no": [
+        {ORTH: "papa'no", LEMMA: "papaano"}],
+    "'di": [
+        {ORTH: "'di", LEMMA: "hindi"}]
+}
+
+
+# To keep things clean and readable, it's recommended to only declare the
+# TOKENIZER_EXCEPTIONS at the bottom:
+
+TOKENIZER_EXCEPTIONS = _exc