StanfordNLP - Code

parts_of_speech.py

#dictionary to hold pos tags and their explanations
pos_dict = {
'CC': 'coordinating conjunction',
'CD': 'cardinal digit',
'DT': 'determiner',
'EX': 'existential there (like: \"there is\" ... think of it like \"there exists\")',
'FW': 'foreign word',
'IN':  'preposition/subordinating conjunction',
'JJ': 'adjective \'big\'',
'JJR': 'adjective, comparative \'bigger\'',
'JJS': 'adjective, superlative \'biggest\'',
'LS': 'list marker 1)',
'MD': 'modal could, will',
'NN': 'noun, singular \'desk\'',
'NNS': 'noun plural \'desks\'',
'NNP': 'proper noun, singular \'Harrison\'',
'NNPS': 'proper noun, plural \'Americans\'',
'PDT': 'predeterminer \'all the kids\'',
'POS': 'possessive ending parent\'s',
'PRP': 'personal pronoun I, he, she',
'PRP$': 'possessive pronoun my, his, hers',
'RB': 'adverb very, silently,',
'RBR': 'adverb, comparative better',
'RBS': 'adverb, superlative best',
'RP': 'particle give up',
'TO': 'to go \'to\' the store.',
'UH': 'interjection errrrrrrrm',
'VB': 'verb, base form take',
'VBD': 'verb, past tense took',
'VBG': 'verb, gerund/present participle taking',
'VBN': 'verb, past participle taken',
'VBP': 'verb, sing. present, non-3d take',
'VBZ': 'verb, 3rd person sing. present takes',
'WDT': 'wh-determiner which',
'WP': 'wh-pronoun who, what',
'WP$': 'possessive wh-pronoun whose',
'WRB': 'wh-abverb where, when',
'QF' : 'quantifier, bahut, thoda, kam (Hindi)',
'VM' : 'main verb',
'PSP' : 'postposition, common in indian langs',
'DEM' : 'demonstrative, common in indian langs'
}

def extract_pos(doc):
    parsed_text = {'word':[], 'pos':[], 'exp':[]}
    for sent in doc.sentences:
        for wrd in sent.words:
            if wrd.pos in pos_dict.keys():
                pos_exp = pos_dict[wrd.pos]
            else:
                pos_exp = 'NA'
            parsed_text['word'].append(wrd.text)
            parsed_text['pos'].append(wrd.pos)
            parsed_text['exp'].append(pos_exp)
    return pd.DataFrame(parsed_text)

extract_pos(doc)