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Merge pull request #42 from LuminosoInsight/mecab-finder
Look for MeCab dictionaries in various places besides this package Former-commit-id: 6f97d5ac099e9bb1a13ccfe114e0f4a79fb9b628
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Andrew Lin
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README.md
74
README.md
@ -1,4 +1,5 @@
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Tools for working with word frequencies from various corpora.
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wordfreq is a Python library for looking up the frequencies of words in many
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languages, based on many sources of data.
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Author: Robyn Speer
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Author: Robyn Speer
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@ -15,31 +16,76 @@ or by getting the repository and running its setup.py:
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python3 setup.py install
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python3 setup.py install
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Japanese and Chinese have additional external dependencies so that they can be
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tokenized correctly.
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To be able to look up word frequencies in Japanese, you need to additionally
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## Additional CJK installation
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install mecab-python3, which itself depends on libmecab-dev and its dictionary.
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These commands will install them on Ubuntu:
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sudo apt-get install mecab-ipadic-utf8 libmecab-dev
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Chinese, Japanese, and Korean have additional external dependencies so that
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pip3 install mecab-python3
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they can be tokenized correctly. Here we'll explain how to set them up,
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in increasing order of difficulty.
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### Chinese
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To be able to look up word frequencies in Chinese, you need Jieba, a
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To be able to look up word frequencies in Chinese, you need Jieba, a
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pure-Python Chinese tokenizer:
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pure-Python Chinese tokenizer:
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pip3 install jieba
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pip3 install jieba
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These dependencies can also be requested as options when installing wordfreq.
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For example:
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pip3 install wordfreq[mecab,jieba]
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### Japanese
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We use MeCab, by Taku Kudo, to tokenize Japanese. To use this in wordfreq, three
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things need to be installed:
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* The MeCab development library (called `libmecab-dev` on Ubuntu)
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* The UTF-8 version of the `ipadic` Japanese dictionary
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(called `mecab-ipadic-utf8` on Ubuntu)
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* The `mecab-python3` Python interface
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To install these three things on Ubuntu, you can run:
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```sh
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sudo apt-get install libmecab-dev mecab-ipadic-utf8
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pip3 install mecab-python3
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```
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If you choose to install `ipadic` from somewhere else or from its source code,
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be sure it's configured to use UTF-8. By default it will use EUC-JP, which will
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give you nonsense results.
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### Korean
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Korean also uses MeCab, with a Korean dictionary package by Yongwoon Lee and
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Yungho Yu. This dictionary is not available as an Ubuntu package.
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Here's a process you can use to install the Korean dictionary and the other
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MeCab dependencies:
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```sh
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sudo apt-get install libmecab-dev mecab-utils
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pip3 install mecab-python3
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wget https://bitbucket.org/eunjeon/mecab-ko-dic/downloads/mecab-ko-dic-2.0.1-20150920.tar.gz
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tar xvf mecab-ko-dic-2.0.1-20150920.tar.gz
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cd mecab-ko-dic-2.0.1-20150920
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./autogen.sh
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make
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sudo make install
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```
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If wordfreq cannot find the Japanese or Korean data for MeCab when asked to
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tokenize those languages, it will raise an error and show you the list of
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paths it searched.
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Sorry that this is difficult. We tried to just package the data files we need
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with wordfreq, like we do for Chinese, but PyPI would reject the package for
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being too large.
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## Usage
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## Usage
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wordfreq provides access to estimates of the frequency with which a word is
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wordfreq provides access to estimates of the frequency with which a word is
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used, in 18 languages (see *Supported languages* below).
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used, in 27 languages (see *Supported languages* below).
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It provides three kinds of pre-built wordlists:
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It provides three kinds of pre-built wordlists:
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@ -288,10 +334,6 @@ The terms of use of this data are:
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acknowledgement of Google Books Ngram Viewer as the source, and inclusion
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acknowledgement of Google Books Ngram Viewer as the source, and inclusion
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of a link to http://books.google.com/ngrams, would be appreciated.
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of a link to http://books.google.com/ngrams, would be appreciated.
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`wordfreq` uses MeCab, by Taku Kudo, plus Korean data files by Yongwoon Lee and
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Yungho Yu. The Korean data is under an Apache 2 license, a copy of which
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appears in wordfreq/data/mecab-ko-dic/COPYING.
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`wordfreq` also contains data derived from the following Creative Commons-licensed
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`wordfreq` also contains data derived from the following Creative Commons-licensed
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sources:
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sources:
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Binary file not shown.
Binary file not shown.
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;
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; Configuration file of IPADIC
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;
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; $Id: dicrc,v 1.4 2006/04/08 06:41:36 taku-ku Exp $;
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;
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cost-factor = 800
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bos-feature = BOS/EOS,*,*,*,*,*,*,*,*
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eval-size = 8
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unk-eval-size = 4
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config-charset = UTF-8
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; yomi
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node-format-yomi = %pS%f[7]
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unk-format-yomi = %M
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eos-format-yomi = \n
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; simple
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node-format-simple = %m\t%F-[0,1,2,3]\n
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eos-format-simple = EOS\n
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; ChaSen
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node-format-chasen = %m\t%f[7]\t%f[6]\t%F-[0,1,2,3]\t%f[4]\t%f[5]\n
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unk-format-chasen = %m\t%m\t%m\t%F-[0,1,2,3]\t\t\n
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eos-format-chasen = EOS\n
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||||||
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; ChaSen (include spaces)
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node-format-chasen2 = %M\t%f[7]\t%f[6]\t%F-[0,1,2,3]\t%f[4]\t%f[5]\n
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unk-format-chasen2 = %M\t%m\t%m\t%F-[0,1,2,3]\t\t\n
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eos-format-chasen2 = EOS\n
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c926154d533ccaef1515af6883056d69c34ca239
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Apache License
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;
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; Configuration file of mecab-ko-dic
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;
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# 비용 값으로 변환할 때 배율 팩터입니다. 700에서 800에서 문제가 없습니다.
|
|
||||||
cost-factor = 800
|
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||||||
# 문장의 시작, 문장 끝에 대한 소성(素性)입니다. CSV로 표현합니다.
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|
||||||
bos-feature = BOS/EOS,*,*,*,*,*,*,*,*
|
|
||||||
# 알려진 단어의 경우 소성(素性)의 처음부터 몇 개까지 일치하면 정답으로
|
|
||||||
# 인정하는지를 지정합니다. 일반적으로 알려진 단어는 품사 활용 등의 정보만
|
|
||||||
# 맞추면 되기 때문에, "읽기", "발음" 소성(素性)은 무시하도록 합니다.
|
|
||||||
# 여기에서는 3가지가 평가됩니다.
|
|
||||||
eval-size = 4
|
|
||||||
# 알 수 없는 단어의 경우
|
|
||||||
# 소성의 처음부터 몇 개까지 일치하면 정답으로 인정할지를 지정합니다.
|
|
||||||
unk-eval-size = 2
|
|
||||||
# dicrc, char.def, unk.def, pos-id.def 파일의 문자 코드셋입니다.
|
|
||||||
config-charset = UTF-8
|
|
||||||
# 좌측에 공백을 포함하는 품사의 연접 비용을 늘리기 위한 설정입니다.
|
|
||||||
# mecab-ko에서만 사용되는 설정입니다. 다음과 같은 형식을 가집니다.
|
|
||||||
# <posid 1>,<posid 1 penalty cost>,<posid 2>,<posid 2 penalty cost>...
|
|
||||||
#
|
|
||||||
# 예) 120,6000 => posid가 120인 품사(조사)의 좌측에 공백을 포함할 경우
|
|
||||||
# 연접 비용을 6000만큼 늘림
|
|
||||||
left-space-penalty-factor = 100,3000,120,6000,172,3000,183,3000,184,3000,185,3000,200,3000,210,6000,220,3000,221,3000,222,3000,230,3000
|
|
||||||
File diff suppressed because it is too large
Load Diff
@ -1 +0,0 @@
|
|||||||
2dbb57fe707d7dddd2392526aad7cbac77378bb3
|
|
||||||
@ -1 +0,0 @@
|
|||||||
58619494b4f81190218b76d9d2090607830e51ec
|
|
||||||
@ -1,66 +0,0 @@
|
|||||||
UNKNOWN,*,*,*,*,*,*,*,* 0
|
|
||||||
*,*,*,*,Compound,*,*,*,* 1
|
|
||||||
*,*,*,*,Inflect,EC,*,*,* 200
|
|
||||||
*,*,*,*,Inflect,EF,*,*,* 200
|
|
||||||
*,*,*,*,Inflect,EP,*,*,* 200
|
|
||||||
*,*,*,*,Inflect,ETM,*,*,* 200
|
|
||||||
*,*,*,*,Inflect,ETN,*,*,* 200
|
|
||||||
*,*,*,*,Inflect,JC,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JKB,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JKC,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JKG,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JKO,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JKQ,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JKS,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JKV,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,JX,*,*,* 210
|
|
||||||
*,*,*,*,Inflect,XSA,*,*,* 220
|
|
||||||
*,*,*,*,Inflect,XSN,*,*,* 221
|
|
||||||
*,*,*,*,Inflect,XSV,*,*,* 222
|
|
||||||
*,*,*,*,Inflect,VCP,*,*,* 230
|
|
||||||
*,*,*,*,Inflect,*,*,*,* 2
|
|
||||||
*,*,*,*,Preanalysis,*,*,*,* 3
|
|
||||||
EC,*,*,*,*,*,*,*,* 100
|
|
||||||
EF,*,*,*,*,*,*,*,* 100
|
|
||||||
EP,*,*,*,*,*,*,*,* 100
|
|
||||||
ETM,*,*,*,*,*,*,*,* 100
|
|
||||||
ETN,*,*,*,*,*,*,*,* 100
|
|
||||||
IC,*,*,*,*,*,*,*,* 110
|
|
||||||
JC,*,*,*,*,*,*,*,* 120
|
|
||||||
JKB,*,*,*,*,*,*,*,* 120
|
|
||||||
JKC,*,*,*,*,*,*,*,* 120
|
|
||||||
JKG,*,*,*,*,*,*,*,* 120
|
|
||||||
JKO,*,*,*,*,*,*,*,* 120
|
|
||||||
JKQ,*,*,*,*,*,*,*,* 120
|
|
||||||
JKS,*,*,*,*,*,*,*,* 120
|
|
||||||
JKV,*,*,*,*,*,*,*,* 120
|
|
||||||
JX,*,*,*,*,*,*,*,* 120
|
|
||||||
MAG,*,*,*,*,*,*,*,* 130
|
|
||||||
MAJ,*,*,*,*,*,*,*,* 131
|
|
||||||
MM,*,*,*,*,*,*,*,* 140
|
|
||||||
NNG,*,*,*,*,*,*,*,* 150
|
|
||||||
NNP,*,*,*,*,*,*,*,* 150
|
|
||||||
NNB,*,*,*,*,*,*,*,* 150
|
|
||||||
NNBC,*,*,*,*,*,*,*,* 150
|
|
||||||
NP,*,*,*,*,*,*,*,* 150
|
|
||||||
NR,*,*,*,*,*,*,*,* 150
|
|
||||||
SF,*,*,*,*,*,*,*,* 160
|
|
||||||
SH,*,*,*,*,*,*,*,* 161
|
|
||||||
SL,*,*,*,*,*,*,*,* 162
|
|
||||||
SN,*,*,*,*,*,*,*,* 163
|
|
||||||
SP,*,*,*,*,*,*,*,* 164
|
|
||||||
SSC,*,*,*,*,*,*,*,* 165
|
|
||||||
SSO,*,*,*,*,*,*,*,* 166
|
|
||||||
SC,*,*,*,*,*,*,*,* 167
|
|
||||||
SY,*,*,*,*,*,*,*,* 168
|
|
||||||
SE,*,*,*,*,*,*,*,* 169
|
|
||||||
VA,*,*,*,*,*,*,*,* 170
|
|
||||||
VCN,*,*,*,*,*,*,*,* 171
|
|
||||||
VCP,*,*,*,*,*,*,*,* 172
|
|
||||||
VV,*,*,*,*,*,*,*,* 173
|
|
||||||
VX,*,*,*,*,*,*,*,* 174
|
|
||||||
XPN,*,*,*,*,*,*,*,* 181
|
|
||||||
XR,*,*,*,*,*,*,*,* 182
|
|
||||||
XSA,*,*,*,*,*,*,*,* 183
|
|
||||||
XSN,*,*,*,*,*,*,*,* 184
|
|
||||||
XSV,*,*,*,*,*,*,*,* 185
|
|
||||||
@ -1,51 +0,0 @@
|
|||||||
# Feature(POS) to Internal State mapping
|
|
||||||
#
|
|
||||||
# 소성(素性)열에서 내부 상태 소생(素生)열로 변환하는 매핑을 정의합니다.
|
|
||||||
#
|
|
||||||
# CRF는 unigram, 왼쪽 문맥 bigram, 오른쪽 문맥 bigram의 3가지 정보를 사용하여
|
|
||||||
# 통계를 계산합니다
|
|
||||||
#
|
|
||||||
# 각 섹션 다음에 한 줄에 하나의 매핑 규칙이 계속됩니다.
|
|
||||||
#
|
|
||||||
# 일치패턴 대상(変換先)
|
|
||||||
#
|
|
||||||
# 일치패턴에는 간단한 정규식을 사용할 수 있습니다.
|
|
||||||
#
|
|
||||||
# * : 모든 문자열과 일치
|
|
||||||
# (AB|CD|EF) : AB 또는 CD 또는 EF 일치
|
|
||||||
# AB : 문자열 AB에만 완전 매치
|
|
||||||
#
|
|
||||||
# 대상(変換先)은 $1 $2, $3..라는 매크로를 사용하여 소생(素生)의
|
|
||||||
# 각 요소(CSV로 표시된 요소)의 내용을 참조할 수 있습니다.
|
|
||||||
#
|
|
||||||
# 품사태그,종성유무,표기,타입,첫번째품사,마지막품사,원형
|
|
||||||
#
|
|
||||||
# Unigram 내부 상태에 대한 매핑
|
|
||||||
[unigram rewrite]
|
|
||||||
*,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,$9
|
|
||||||
|
|
||||||
# 왼쪽 문맥 bigram 내부 상태에 대한 매핑
|
|
||||||
# 기본으로 의미부류($2)까지 표현한다.
|
|
||||||
# 조사외 몇 가지의 품사에서는 품사,의미부로,읽기($1,$2,*,$4)로 표현한다.
|
|
||||||
# 하늘/NNG,T,*,*,*,*,* + 은/J,*,은,*,*,*,*
|
|
||||||
#
|
|
||||||
[left rewrite]
|
|
||||||
BOS/EOS,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
|
|
||||||
SF,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
|
|
||||||
*,*,*,*,Inflect,(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|VCP|ETM|XSN),*,*,* $6,$2,*,$4,*,*,*,*,*
|
|
||||||
*,*,*,*,(Inflect|Preanalysis),*,*,*,* $6,$2,*,*,*,*,*,*,*
|
|
||||||
(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|VCP|ETM|XSN),*,*,*,*,*,*,*,* $1,$2,*,$4,*,*,*,*,*
|
|
||||||
*,*,*,*,*,*,*,*,* $1,$2,*,*,*,*,*,*,*
|
|
||||||
|
|
||||||
# 오른쪽 문맥 bigram 내부 상태에 대한 매핑
|
|
||||||
# 기본으로 종성유무($3)까지 표현한다.
|
|
||||||
# 조사외 몇 가지의 품사에서는 품사,의미,종성유무,읽기($1,$2,$3,$4)로 표현한다.
|
|
||||||
# ex) 하늘/NN,T,*,*,*,*,* + 은/J,T,은,*,*,*,*
|
|
||||||
[right rewrite]
|
|
||||||
BOS/EOS,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
|
|
||||||
SF,*,*,*,*,*,*,*,* $1,$2,$3,$4,$5,$6,$7,$8,BOS/EOS
|
|
||||||
SL,*,*,*,*,*,*,*,* NNG,$2,$3,*,*,*,*,*,*
|
|
||||||
*,*,*,*,Inflect,*,(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|XSN),*,* $7,$2,$3,$4,*,*,*,*,*
|
|
||||||
*,*,*,*,(Inflect|Preanalysis),*,*,*,* $7,$2,$3,*,*,*,*,*,*
|
|
||||||
(JC|JKB|JKC|JKG|JKO|JKQ|JKS|JKV|JX|NNB|NNBC|XSN),*,*,*,*,*,*,*,* $1,$2,$3,$4,*,*,*,*,*
|
|
||||||
*,*,*,*,*,*,*,*,* $1,$2,$3,*,*,*,*,*,*
|
|
||||||
File diff suppressed because it is too large
Load Diff
@ -1 +0,0 @@
|
|||||||
9655d23c3a0900764cbcdb8d8395d0f09ec098ed
|
|
||||||
Binary file not shown.
@ -1,12 +1,61 @@
|
|||||||
from pkg_resources import resource_filename
|
from pkg_resources import resource_filename
|
||||||
import MeCab
|
import MeCab
|
||||||
import unicodedata
|
import unicodedata
|
||||||
|
import os
|
||||||
|
|
||||||
|
|
||||||
|
# MeCab has fixed-sized buffers for many things, including the dictionary path
|
||||||
|
MAX_PATH_LENGTH = 58
|
||||||
|
|
||||||
|
|
||||||
|
def find_mecab_dictionary(names):
|
||||||
|
"""
|
||||||
|
Find a MeCab dictionary with a given name. The dictionary has to be
|
||||||
|
installed separately -- see wordfreq's README for instructions.
|
||||||
|
"""
|
||||||
|
suggested_pkg = names[0]
|
||||||
|
paths = [
|
||||||
|
os.path.expanduser('~/.local/lib/mecab/dic'),
|
||||||
|
'/var/lib/mecab/dic',
|
||||||
|
'/var/local/lib/mecab/dic',
|
||||||
|
'/usr/lib/mecab/dic',
|
||||||
|
'/usr/local/lib/mecab/dic',
|
||||||
|
]
|
||||||
|
full_paths = [os.path.join(path, name) for path in paths for name in names]
|
||||||
|
checked_paths = [path for path in full_paths if len(path) <= MAX_PATH_LENGTH]
|
||||||
|
for path in checked_paths:
|
||||||
|
if os.path.exists(path):
|
||||||
|
return path
|
||||||
|
|
||||||
|
error_lines = [
|
||||||
|
"Couldn't find the MeCab dictionary named %r." % suggested_pkg,
|
||||||
|
"You should download or use your system's package manager to install",
|
||||||
|
"the %r package." % suggested_pkg,
|
||||||
|
"",
|
||||||
|
"We looked in the following locations:"
|
||||||
|
] + ["\t%s" % path for path in checked_paths]
|
||||||
|
|
||||||
|
skipped_paths = [path for path in full_paths if len(path) > MAX_PATH_LENGTH]
|
||||||
|
if skipped_paths:
|
||||||
|
error_lines += [
|
||||||
|
"We had to skip these paths that are too long for MeCab to find:",
|
||||||
|
] + ["\t%s" % path for path in skipped_paths]
|
||||||
|
|
||||||
|
raise OSError('\n'.join(error_lines))
|
||||||
|
|
||||||
|
|
||||||
|
def make_mecab_analyzer(names):
|
||||||
|
"""
|
||||||
|
Get a MeCab analyzer object, given a list of names the dictionary might
|
||||||
|
have.
|
||||||
|
"""
|
||||||
|
return MeCab.Tagger('-d %s' % find_mecab_dictionary(names))
|
||||||
|
|
||||||
|
|
||||||
# Instantiate the MeCab analyzers for each language.
|
# Instantiate the MeCab analyzers for each language.
|
||||||
MECAB_ANALYZERS = {
|
MECAB_ANALYZERS = {
|
||||||
'ja': MeCab.Tagger('-d %s' % resource_filename('wordfreq', 'data/mecab-ja-ipadic')),
|
'ja': make_mecab_analyzer(['mecab-ipadic-utf8', 'ipadic-utf8']),
|
||||||
'ko': MeCab.Tagger('-d %s' % resource_filename('wordfreq', 'data/mecab-ko-dic'))
|
'ko': make_mecab_analyzer(['mecab-ko-dic', 'ko-dic'])
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user