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Polyglot is a natural language pipeline that supports massive multilingual applications.
Features
- Tokenization (165 Languages)
- Language detection (196 Languages)
- Named Entity Recognition (40 Languages)
- Part of Speech Tagging (16 Languages)
- Sentiment Analysis (136 Languages)
- Word Embeddings (137 Languages)
- Morphological analysis (135 Languages)
- Transliteration (69 Languages)
Developerrmyeid gmail com.. code:: python
import polyglot
from polyglot.text import Text, WordLanguage Detection
.. code:: python
text = Text("Bonjour, Mesdames.")
print("Language Detected: Code={}, Name={}\n".format(text.language.code, text.language.name))
.. parsed-literal::
Language Detected: Code=fr, Name=French
Tokenization.. code:: python
zen = Text("Beautiful is better than ugly. "
"Explicit is better than implicit. "
"Simple is better than complex.")
print(zen.words).. parsed-literal::
[u'Beautiful', u'is', u'better', u'than', u'ugly', u'.', u'Explicit', u'is', u'better', u'than', u'implicit', u'.', u'Simple', u'is', u'better', u'than', u'complex', u'.'].. code:: python
print(zen.sentences).. parsed-literal::
[Sentence("Beautiful is better than ugly."), Sentence("Explicit is better than implicit."), Sentence("Simple is better than complex.")]Part of Speech Tagging
.. code:: python
text = Text(u"O primeiro uso de desobediência civil em massa ocorreu em setembro de 1906.")
print("{:<16}{}".format("Word", "POS Tag")+"\n"+"-"*30)
for word, tag in text.pos_tags:
print(u"{:<16}{:>2}".format(word, tag))
.. parsed-literal::
Word POS Tag
------------------------------
O DET
primeiro ADJ
uso NOUN
de ADP
desobediência NOUN
civil ADJ
em ADP
massa NOUN
ocorreu ADJ
em ADP
setembro NOUN
de ADP
1906 NUM
. PUNCT
Named Entity Recognition.. code:: python
text = Text(u"In Großbritannien war Gandhi mit dem westlichen Lebensstil vertraut geworden")
print(text.entities).. parsed-literal::
[I-LOC([u'Gro\\xdfbritannien']), I-PER([u'Gandhi'])]Polarity
.. code:: python
print("{:<16}{}".format("Word", "Polarity")+"\n"+"-"*30)
for w in zen.words[:6]:
print("{:<16}{:>2}".format(w, w.polarity))
.. parsed-literal::
Word Polarity
------------------------------
Beautiful 0
is 0
better 1
than 0
ugly -1
. 0
Embeddings.. code:: python
word = Word("Obama", language="en")
print("Neighbors (Synonms) of {}".format(word)+"\n"+"-"*30)
for w in word.neighbors:
print("{:<16}".format(w))
print("\n\nThe first 10 dimensions out the {} dimensions\n".format(word.vector.shape[0]))
print(word.vector[:10]).. parsed-literal::
Neighbors (Synonms) of Obama
------------------------------
Bush
Reagan
Clinton
Ahmadinejad
Nixon
Karzai
McCain
Biden
Huckabee
Lula
The first 10 dimensions out the 256 dimensions
[-2.57382345 1.52175975 0.51070285 1.08678675 -0.74386948 -1.18616164
2.92784619 -0.25694436 -1.40958667 -2.39675403]Morphology
.. code:: python
word = Text("Preprocessing is an essential step.").words[0]
print(word.morphemes)
.. parsed-literal::
[u'Pre', u'process', u'ing']
Transliteration.. code:: python
from polyglot.transliteration import Transliterator
transliterator = Transliterator(source_lang="en", target_lang="ru")
print(transliterator.transliterate(u"preprocessing")).. parsed-literal::
препрокессинг