I wrote a corpus reader that reads the results of MeCab analysis

Imitating chasen.py written by mhagiwara for studying mecab. py was written.

mecab.py

It is assumed that NLTK and nltk_data have been installed and downloaded. Place the data under nltk_data / corpus or create a symbolic link.

import nltk
corpora_path = nltk.data.find('corpora/test')
"""
your data must be stored or linked in nltk/corpora
"""

fileids = r'.*\.mecab'
"""
:param corpus name: regular expression or list of corpus name.
:type corpus: list or strings
"""

reader = MeCabCorpusReader(corpora_path, fileids, encoding='utf8')
print reader.raw()
print ', '.join(reader.words())
for w, t in reader.tagged_words():
    print w, t
for para in reader.paras():
    for sent in para:
        for word in sent:
            print word
for para in reader.tagged_paras():
    for sent in para:
        for (word, pos) in sent:
            print word, pos

corpus / test is a directory containing files that have been analyzed by MeCab and has the extension mecab. The contents of the file look like this.

Plum noun,General,*,*,*,*,Plum,Plum,Plum
Also particles,Particle,*,*,*,*,Also,Mo,Mo
Peach noun,General,*,*,*,*,Peaches,peach,peach
Also particles,Particle,*,*,*,*,Also,Mo,Mo
Peach noun,General,*,*,*,*,Peaches,peach,peach
Particles,Attributive,*,*,*,*,of,No,No
Noun,Non-independent,Adverbs possible,*,*,*,home,Uchi,Uchi
EOS

The output is

raw()
Plum noun,General,*,*,*,*,Plum,Plum,Plum
Also particles,Particle,*,*,*,*,Also,Mo,Mo
Peach noun,General,*,*,*,*,Peaches,peach,peach
Also particles,Particle,*,*,*,*,Also,Mo,Mo
Peach noun,General,*,*,*,*,Peaches,peach,peach
Particles,Attributive,*,*,*,*,of,No,No
Noun,Non-independent,Adverbs possible,*,*,*,home,Uchi,Uchi
EOS

words()
Plum,Also,Alsoも,Also,Alsoも,of,home

tagged_words()
Plum info:noun,General,*,*,*,*,Plum,Plum,Plum
Also info:Particle,Particle,*,*,*,*,Also,Mo,Mo
Peach info:noun,General,*,*,*,*,Peaches,peach,peach
Also info:Particle,Particle,*,*,*,*,Also,Mo,Mo
Peach info:noun,General,*,*,*,*,Peaches,peach,peach
Info:Particle,Attributive,*,*,*,*,of,No,No
Of info:noun,Non-independent,Adverbs possible,*,*,*,home,Uchi,Uchi

paras()
Plum
Also
Peaches
Also
Peaches
of
home

tagged_paras()
Plum info:noun,General,*,*,*,*,Plum,Plum,Plum
Also info:Particle,Particle,*,*,*,*,Also,Mo,Mo
Peach info:noun,General,*,*,*,*,Peaches,peach,peach
Also info:Particle,Particle,*,*,*,*,Also,Mo,Mo
Peach info:noun,General,*,*,*,*,Peaches,peach,peach
Info:Particle,Attributive,*,*,*,*,of,No,No
Of info:noun,Non-independent,Adverbs possible,*,*,*,home,Uchi,Uchi

Recommended Posts

I wrote a corpus reader that reads the results of MeCab analysis

I wrote a script that splits the image in two

Create a bot that only returns the result of morphological analysis with MeCab on Discord

I made a slack bot that notifies me of the temperature

I analyzed the image of the Kyudo scoring book (a booklet that records the results of the hits). (Google Colaboratory)

I made a calendar that automatically updates the distribution schedule of Vtuber

The story of developing a web application that automatically generates catchphrases [MeCab]

I tried cluster analysis of the weather map

A memo that I wrote a quicksort in Python

The story of IPv6 address that I want to keep at a minimum

I wrote a PyPI module that extends the parameter style in Python's sqlite3 module