The NLTK
documentation is rather poor in this integration. The steps I followed were:
Download http://nlp.stanford.edu/software/stanford-postagger-
Try:
# StanfordPOSTagger
from nltk.tag.stanford import StanfordPOSTagger
stanford_dir = '/home/me/stanford/stanford-postagger-full-2015-04-20/'
modelfile = stanford_dir + 'models/english-bidirectional-distsim.tagger'
jarfile = stanford_dir + 'stanford-postagger.jar'
st = StanfordPOSTagger(model_filename=modelfile, path_to_jar=jarfile)
# NERTagger
stanford_dir = '/home/me/stanford/stanford-ner-2015-04-20/'
jarfile = stanford_dir + 'stanford-ner.jar'
modelfile = stanford_dir + 'classifiers/english.all.3class.distsim.crf.ser.gz'
st = StanfordNERTagger(model_filename=modelfile, path_to_jar=jarfile)
For detailed information on NLTK API with Stanford tools, take a look at: https://github.com/nltk/nltk/wiki/Installing-Third-Party-Software#stanford-tagger-ner-tokenizer-and-parser
Note: The NLTK APIs are for the individual Stanford tools, if you're using Stanford Core NLP, it's best to follow @dimazest instructions on http://www.eecs.qmul.ac.uk/~dm303/stanford-dependency-parser-nltk-and-anaconda.html
As for Spanish NER Tagging, I strongly suggest that you us Stanford Core NLP (http://nlp.stanford.edu/software/corenlp.shtml) instead of using the Stanford NER package (http://nlp.stanford.edu/software/CRF-NER.shtml). And follow @dimazest solution for JSON file reading.
Alternatively, if you must use the NER packge, you can try following the instructions from https://github.com/alvations/nltk_cli (Disclaimer: This repo is not affiliated with NLTK officially). Do the following on the unix command line:
cd $HOME
wget http://nlp.stanford.edu/software/stanford-spanish-corenlp-2015-01-08-models.jar
unzip stanford-spanish-corenlp-2015-01-08-models.jar -d stanford-spanish
cp stanford-spanish/edu/stanford/nlp/models/ner/* /home/me/stanford/stanford-ner-2015-04-20/ner/classifiers/
Then in python:
# NERTagger
stanford_dir = '/home/me/stanford/stanford-ner-2015-04-20/'
jarfile = stanford_dir + 'stanford-ner.jar'
modelfile = stanford_dir + 'classifiers/spanish.ancora.distsim.s512.crf.ser.gz'
st = StanfordNERTagger(model_filename=modelfile, path_to_jar=jarfile)