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From "Jim Ferenczi (JIRA)" <>
Subject [jira] [Commented] (LUCENE-8231) Nori, a Korean analyzer based on mecab-ko-dic
Date Wed, 04 Apr 2018 09:06:00 GMT


Jim Ferenczi commented on LUCENE-8231:

Hi Robert,
I pushed another iteration that moves the decompound process and the POS filtering in the
tokenizer. I think it's simpler to perform the decompound and the filtering directly in the
tokenizer, this also allows to keep the compound token (I added a decompound mode option that
disallow decompound (none), discard the decompound (discard) or perform the decompound and
keep the original token (mixed)). By default the compound token is discarded but it can be
kept using the mixed mode. 
I also changed the normalization option when building the dictionary, instead of adding the
normalized form and the original form the builder now replaces the original form with the
normalized one. By default the normalization is not activated but it can be useful for other
Korean dictionaries that uses a decomposed form for hanguls like the Handic for instance:
I added more tests and javadocs, I think it's getting closer ;)

> Nori, a Korean analyzer based on mecab-ko-dic
> ---------------------------------------------
>                 Key: LUCENE-8231
>                 URL:
>             Project: Lucene - Core
>          Issue Type: New Feature
>            Reporter: Jim Ferenczi
>            Priority: Major
>         Attachments: LUCENE-8231-remap-hangul.patch, LUCENE-8231.patch, LUCENE-8231.patch,
LUCENE-8231.patch, LUCENE-8231.patch, LUCENE-8231.patch
> There is a dictionary similar to IPADIC but for Korean called mecab-ko-dic:
> It is available under an Apache license here:
> This dictionary was built with MeCab, it defines a format for the features adapted for
the Korean language.
> Since the Kuromoji tokenizer uses the same format for the morphological analysis (left
cost + right cost + word cost) I tried to adapt the module to handle Korean with the mecab-ko-dic.
I've started with a POC that copies the Kuromoji module and adapts it for the mecab-ko-dic.
> I used the same classes to build and read the dictionary but I had to make some modifications
to handle the differences with the IPADIC and Japanese. 
> The resulting binary dictionary takes 28MB on disk, it's bigger than the IPADIC but mainly
because the source is bigger and there are a lot of
> compound and inflect terms that define a group of terms and the segmentation that can
be applied. 
> I attached the patch that contains this new Korean module called -godori- nori. It is
an adaptation of the Kuromoji module so currently
> the two modules don't share any code. I wanted to validate the approach first and check
the relevancy of the results. I don't speak Korean so I used the relevancy
> tests that was added for another Korean tokenizer (
and tested the output against mecab-ko which is the official fork of mecab to use the mecab-ko-dic.
> I had to simplify the JapaneseTokenizer, my version removes the nBest output and the
decomposition of too long tokens. I also
> modified the handling of whitespaces since they are important in Korean. Whitespaces
that appear before a term are attached to that term and this
> information is used to compute a penalty based on the Part of Speech of the token. The
penalty cost is a feature added to mecab-ko to handle 
> morphemes that should not appear after a morpheme and is described in the mecab-ko page:
> Ignoring whitespaces is also more inlined with the official MeCab library which attach
the whitespaces to the term that follows.
> I also added a decompounder filter that expand the compounds and inflects defined in
the dictionary and a part of speech filter similar to the Japanese
> that removes the morpheme that are not useful for relevance (suffix, prefix, interjection,
...). These filters don't play well with the tokenizer if it can 
> output multiple paths (nBest output for instance) so for simplicity I removed this ability
and the Korean tokenizer only outputs the best path.
> I compared the result with mecab-ko to confirm that the analyzer is working and ran the
relevancy test that is defined in included
> in the patch (written by Robert for another Korean analyzer). Here are the results:
> ||Analyzer||Index Time||Index Size||MAP(CLASSIC)||MAP(BM25)||MAP(GL2)||
> |Standard|35s|131MB|.007|.1044|.1053|
> |CJK|36s|164MB|.1418|.1924|.1916|
> |Korean|212s|90MB|.1628|.2094|.2078|
> I find the results very promising so I plan to continue to work on this project. I started
to extract the part of the code that could be shared with the
> Kuromoji module but I wanted to share the status and this POC first to confirm that this
approach is viable. The advantages of using the same model than
> the Japanese analyzer are multiple: we don't have a Korean analyzer at the moment ;),
the resulting dictionary is small compared to other libraries that
> use the mecab-ko-dic (the FST takes only 5.4MB) and the Tokenizer prunes the lattice
on the fly to select the best path efficiently.
> The dictionary can be built directly from the godori module with the following command:
> ant regenerate (you need to create the resource directory (mkdir lucene/analysis/godori/src/resources/org/apache/lucene/analysis/ko/dict)
first since the dictionary is not included in the patch).
> I've also added some minimal tests in the module to play with the analysis.

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