Basic support for Telugu language (#2751)

.github/contributors/sainathadapa.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
+you grant to us in the contributed materials. The term **"us"** shall mean
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+**"you"** shall mean the person or entity identified below.
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+
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+## Contributor Details
+
+| Field                          | Entry                |
+|------------------------------- | -------------------- |
+| Name                           | Sainath Adapa   |
+| Company name (if applicable)   |                      |
+| Title or role (if applicable)  |                      |
+| Date                           | 2018-09-06           |
+| GitHub username                | sainathadapa         |
+| Website (optional)             |                      |

spacy/lang/te/__init__.py

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+# coding: utf8
+from __future__ import unicode_literals
+
+from .stop_words import STOP_WORDS
+from .lex_attrs import LEX_ATTRS
+
+from ...language import Language
+from ...attrs import LANG
+
+
+class TeluguDefaults(Language.Defaults):
+    lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
+    lex_attr_getters.update(LEX_ATTRS)
+    lex_attr_getters[LANG] = lambda text: 'te'
+    stop_words = STOP_WORDS
+
+
+class Telugu(Language):
+    lang = 'te'
+    Defaults = TeluguDefaults
+
+
+__all__ = ['Telugu']

spacy/lang/te/examples.py

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+# coding: utf8
+from __future__ import unicode_literals
+
+
+"""
+Example sentences to test spaCy and its language models.
+
+>>> from spacy.lang.te import Telugu
+>>> nlp = Telugu()
+>>> from spacy.lang.te.examples import sentences
+>>> docs = nlp.pipe(sentences)
+"""
+
+
+sentences = [
+    "ఆపిల్ 1 బిలియన్ డాలర్స్ కి యూ.కె. స్టార్ట్అప్ ని కొనాలని అనుకుంటుంది.",
+    "ఆటోనోమోస్ కార్లు భీమా బాధ్యతను తయారీదారులపైకి మళ్లిస్తాయి.",
+    "సాన్ ఫ్రాన్సిస్కో కాలిబాట డెలివరీ రోబోట్లను నిషేధించడానికి ఆలోచిస్తుంది.",
+    "లండన్ యునైటెడ్ కింగ్డమ్ లో పెద్ద సిటీ.",
+    "నువ్వు ఎక్కడ ఉన్నావ్?",
+    "ఫ్రాన్స్ అధ్యక్షుడు ఎవరు?",
+    "యునైటెడ్ స్టేట్స్ యొక్క రాజధాని ఏంటి?",
+    "బరాక్ ఒబామా ఎప్పుడు జన్మించారు?"
+]

spacy/lang/te/lex_attrs.py

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+# coding: utf8
+from __future__ import unicode_literals
+
+from ...attrs import LIKE_NUM
+
+_num_words = ['సున్నా', 'శూన్యం', 'ఒకటి',  'రెండు', 'మూడు', 'నాలుగు', 'ఐదు', 'ఆరు',
+              'ఏడు', 'ఎనిమిది', 'తొమ్మిది', 'పది', 'పదకొండు', 'పన్నెండు', 'పదమూడు',
+              'పద్నాలుగు', 'పదిహేను', 'పదహారు', 'పదిహేడు', 'పద్దెనిమిది', 'పందొమ్మిది', 'ఇరవై',
+              'ముప్పై', 'నలభై', 'యాభై', 'అరవై', 'డెబ్బై', 'ఎనభై', 'తొంబై', 'వంద', 'నూరు',
+              'వెయ్యి', 'లక్ష', 'కోటి']
+
+
+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.lower() in _num_words:
+        return True
+    return False
+
+
+LEX_ATTRS = {
+    LIKE_NUM: like_num
+}

spacy/lang/te/stop_words.py

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+# coding: utf8
+from __future__ import unicode_literals
+
+# Source: https://github.com/Xangis/extra-stopwords (MIT License)
+
+STOP_WORDS = set("""
+అందరూ
+అందుబాటులో
+అడగండి
+అడగడం
+అడ్డంగా
+అనుగుణంగా
+అనుమతించు
+అనుమతిస్తుంది
+అయితే
+ఇప్పటికే
+ఉన్నారు
+ఎక్కడైనా
+ఎప్పుడు
+ఎవరైనా
+ఎవరో ఒకరు
+ఏ
+ఏదైనా
+ఏమైనప్పటికి
+ఏమైనప్పటికి
+ఒక
+ఒక ప్రక్కన
+కనిపిస్తాయి
+కాదు
+కాదు
+కూడా
+గా
+గురించి
+చుట్టూ
+చేయగలిగింది
+తగిన
+తర్వాత
+తర్వాత
+దాదాపు
+దూరంగా
+నిజంగా
+పై
+ప్రకారం
+మధ్య
+మధ్య
+మరియు
+మరొక
+మళ్ళీ
+మాత్రమే
+మెచ్చుకో
+వద్ద
+వద్ద
+వెంట
+వేరుగా
+వ్యతిరేకంగా
+సంబంధం
+""".split())