<p>If you are looking for another multilingual POS tagger, you might want to try <a href="http://rdrpostagger.sourceforge.net/" rel="noreferrer">RDRPOSTagger</a>: a robust, easy-to-use and language-independent toolkit for POS and morphological tagging. See experimental results including performance speed and tagging accuracy on 13 languages in <a href="http://arxiv.org/abs/1412.4021" rel="noreferrer">this paper</a>. RDRPOSTagger now supports pre-trained POS and morphological tagging models for Bulgarian, Czech, Dutch, English, French, German, Hindi, Italian, Portuguese, Spanish, Swedish, Thai and Vietnamese. RDRPOSTagger also supports the pre-trained Universal POS tagging models for 40 languages.</p>

<p>In Python, you can utilize the pre-trained models for tagging a raw unlabeled text corpus as:</p>

<p><code>python RDRPOSTagger.py tag PATH-TO-PRETRAINED-MODEL PATH-TO-LEXICON PATH-TO-RAW-TEXT-CORPUS</code></p>

<p>Example: <code>python RDRPOSTagger.py tag ../Models/POS/German.RDR ../Models/POS/German.DICT ../data/GermanRawTest</code></p>

<p>If you would like to program with RDRPOSTagger, please follow code lines 92-98 in <code>RDRPOSTagger.py</code> module in <code>pSCRDRTagger</code> package. Here is an example:</p>

<pre><code>r = RDRPOSTagger()
r.constructSCRDRtreeFromRDRfile("../Models/POS/German.RDR") #Load POS tagging model for German
DICT = readDictionary("../Models/POS/German.DICT") #Load a German lexicon 
r.tagRawSentence(DICT, "Die Reaktion des deutschen Außenministers zeige , daß dieser die außerordentlich wichtige Rolle Irans in der islamischen Welt erkenne .")

r = RDRPOSTagger()
r.constructSCRDRtreeFromRDRfile("../Models/POS/French.RDR") # Load POS tagging model for French
DICT = readDictionary("../Models/POS/French.DICT") # Load a French lexicon
r.tagRawSentence(DICT, "Cette annonce a fait l' effet d' une véritable bombe . ")
</code></pre>
Multilingual NLTK for POS Tagging and Lemmatizer
<p>Recently I approached to the NLP and I tried to use <a href="http://www.nltk.org" rel="noreferrer">NLTK</a> and <a href="http://textblob.readthedocs.org" rel="noreferrer">TextBlob</a> for analyzing texts. I would like to develop an app that analyzes reviews made by travelers and so I have to manage a lot of texts written in different languages. I need to do two main operations: POS Tagging and lemmatization. I have seen that in NLTK there is a possibility to choice the the right language for sentences tokenization like this:</p>

<pre><code>tokenizer = nltk.data.load('tokenizers/punkt/PY3/italian.pickle')
</code></pre>

<p>I haven't found the the right way to set the language for POS Tagging and Lemmatizer in different languages yet. How can I set the correct corpora/dictionary for non-english texts such as Italian, French, Spanish or German? I also see that there is a possibility to import the "TreeBank" or "WordNet" modules, but I don't understand how I can use them.  Otherwise, where can I find the respective corporas?</p>

<p>Can you give me some suggestion or reference? Please take care that I'm not an expert of NLTK.</p>

<p>Many Thanks. </p>