This is an implementation of a plugin for Elasticsearch using the implementation of Nakatani Shuyo's language detector.
It uses 3-gram character and a Bayesian filter with various normalizations and feature sampling. The precision is over 99% for 53 languages.
The plugin offers a mapping type to specify fields where you want to enable language detection. Detected languages are indexed into a subfield of the field named 'lang', as you can see in the example. The field can be queried for language codes.
You can use the multi_field mapping type to combine this plugin with the attachment mapper plugin, to enable language detection in base64-encoded binary data. Currently, UTF-8 texts are supported only.
The plugin offers also a REST endpoint, where a short text can be posted to in UTF-8, and the plugin responds with a list of recognized languages.
Here is a list of languages code recognized:
af ar bg bn cs da de el en es et fa fi fr gu he hi hr hu id it ja kn ko lt lv mk ml mr ne nl no pa pl pt ro ru sk sl so sq sv sw ta te th tl tr uk ur vi zh-cn zh-tw
| Elasticsearch | Plugin | Release date |
|---|---|---|
| 2.0.0 | 2.0.0.0 | Nov 12, 2015 |
| 2.0.0-beta2 | 2.0.0-beta2.0 | Sep 19, 2015 |
| 1.6.0 | 1.6.0.0 | Jul 1, 2015 |
| 1.4.0 | 1.4.4.2 | Apr 3, 2015 |
| 1.4.0 | 1.4.4.1 | Mar 4, 2015 |
| 1.4.0 | 1.4.0.2 | Nov 26, 2014 |
| 1.4.0 | 1.4.0.1 | Nov 20, 2014 |
| 1.4.0 | 1.4.0.0 | Nov 14, 2014 |
| 1.3.1 | 1.3.0.0 | Jul 30, 2014 |
| 1.2.1 | 1.2.1.1 | Jun 18, 2014 |
./bin/plugin -install langdetect -url http://xbib.org/repository/org/xbib/elasticsearch/plugin/elasticsearch-langdetect/1.6.0.0/elasticsearch-langdetect-1.6.0.0-plugin.zip
./bin/plugin install http://xbib.org/repository/org/xbib/elasticsearch/plugin/elasticsearch-langdetect/2.0.0.0/elasticsearch-langdetect-2.0.0.0-plugin.zip
Do not forget to restart the node after installing.
The Maven project site is available at Github
All feedback is welcome! If you find issues, please post them at Github
In this example, we create a simple detector field, and write text to it for detection.
curl -XDELETE 'localhost:9200/test'
curl -XPUT 'localhost:9200/test'
curl -XPOST 'localhost:9200/test/article/_mapping' -d '
{
"article" : {
"properties" : {
"content" : { "type" : "langdetect" }
}
}
}
'
curl -XPUT 'localhost:9200/test/article/1' -d '
{
"title" : "Some title",
"content" : "Oh, say can you see by the dawn`s early light, What so proudly we hailed at the twilight`s last gleaming?"
}
'
curl -XPUT 'localhost:9200/test/article/2' -d '
{
"title" : "Ein Titel",
"content" : "Einigkeit und Recht und Freiheit für das deutsche Vaterland!"
}
'
curl -XPUT 'localhost:9200/test/article/3' -d '
{
"title" : "Un titre",
"content" : "Allons enfants de la Patrie, Le jour de gloire est arrivé!"
}
'
A search for the detected language codes is a simple term query, like this:
curl -XGET 'localhost:9200/test/_refresh'
curl -XPOST 'localhost:9200/test/_search' -d '
{
"query" : {
"term" : {
"content" : "en"
}
}
}
'
curl -XPOST 'localhost:9200/test/_search' -d '
{
"query" : {
"term" : {
"content" : "de"
}
}
}
'
curl -XPOST 'localhost:9200/test/_search' -d '
{
"query" : {
"term" : {
"content" : "fr"
}
}
}
'
Using multifields, it is possible to store the text alongside with the detected language(s). Here, we use another (short nonsense) example text for demonstration, which has more than one detected language code.
curl -XDELETE 'localhost:9200/test'
curl -XPUT 'localhost:9200/test'
curl -XPOST 'localhost:9200/test/article/_mapping' -d '
{
"article" : {
"properties" : {
"content" : {
"type" : "multi_field",
"fields" : {
"content" : {
"type" : "string"
},
"language" : {
"type": "langdetect",
"store" : true
}
}
}
}
}
}
'
curl -XPUT 'localhost:9200/test/article/1' -d '
{
"content" : "watt datt"
}
'
curl -XGET 'localhost:9200/test/_refresh'
curl -XPOST 'localhost:9200/test/_search?pretty' -d '
{
"fields" : "content.language",
"query" : {
"match" : {
"content" : "watt datt"
}
}
}
'
The result is
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 0.51623213,
"hits" : [ {
"_index" : "test",
"_type" : "article",
"_id" : "1",
"_score" : 0.51623213,
"fields" : {
"content.language" : [ "sv", "it", "nl" ]
}
} ]
}
}
curl -XDELETE 'localhost:9200/test'
curl -XPUT 'localhost:9200/test' -d '
{
"mappings" : {
"_default_" : {
"properties" : {
"content" : {
"type" : "attachment",
"fields" : {
"content" : {
"type" : "multi_field",
"fields" : {
"content" : {
"type" : "string"
},
"language" : {
"type" : "langdetect",
"binary" : true
}
}
}
}
}
}
}
}
}
'
rm index.tmp
echo -n '{"content":"' >> index.tmp
echo "This is a very simple text in plain english" | base64 >> index.tmp
echo -n '"}' >> index.tmp
curl -XPOST --data-binary "@index.tmp" 'localhost:9200/test/docs/1'
rm index.tmp
curl -XPOST 'localhost:9200/test/_refresh'
curl -XGET 'localhost:9200/test/docs/_mapping?pretty'
curl -XPOST 'localhost:9200/test/docs/_search?pretty' -d '
{
"query" : {
"match" : {
"content" : "very simple"
}
}
}
'
curl -XPOST 'localhost:9200/test/docs/_search?pretty' -d '
{
"query" : {
"term" : {
"content.language" : "en"
}
}
}
'
curl -XPOST 'localhost:9200/_langdetect?pretty' -d 'This is a test'
{
"profile" : "/langdetect/",
"languages" : [ {
"language" : "en",
"probability" : 0.9999971603535163
} ]
}
curl -XPOST 'localhost:9200/_langdetect?pretty' -d 'Das ist ein Test'
{
"profile" : "/langdetect/",
"languages" : [ {
"language" : "de",
"probability" : 0.9999993070517024
} ]
}
curl -XPOST 'localhost:9200/_langdetect?pretty' -d 'Datt isse ne test'
{
"profile" : "/langdetect/",
"languages" : [ {
"language" : "no",
"probability" : 0.5714251911820175
}, {
"language" : "de",
"probability" : 0.14285762298521493
}, {
"language" : "it",
"probability" : 0.14285706984044144
} ]
}
curl -XPOST 'localhost:9200/_langdetect?pretty&profile=/langdetect/short-text/' -d 'Das ist ein Test'
{
"profile" : "/langdetect/short-text/",
"languages" : [ {
"language" : "de",
"probability" : 0.9999993070517024
} ]
}
These settings can be used in elasticsearch.yml to modify language detection.
Use with caution. You don't need to modify settings. This list is just for the sake of completeness. For successful modification of the model parameters, you should study the source code and be familiar with probabilistic matching using naive bayes with character n-gram. See also Ted Dunning, Statistical Identification of Language, 1994.
langdetect.languages - a comma-separated list of language codes used to restrict the detection
langdetect.map.<code> - a substitution code for a language code
langdetect.number_of_trials - number of trials, affects CPU usage (default: 7)
langdetect.alpha - additional smoothing parameter, default: 0.5
langdetect.alpha_width - the width of smoothing, default: 0.05
langdetect.iteration_limit - safeguard to break loop, default: 10000
langdetect.prob_threshold - default: 0.1
langdetect.conv_threshold - detection is terminated when normalized probability exceeds
this threshold, default: 0.99999
langdetect.base_freq - default 10000
Thanks to Alexander Reelsen for his OpenNLP plugin, from where I have copied and adapted the mapping type analysis code.
Elasticsearch Langdetect Plugin
Derived work of language-detection by Nakatani Shuyo http://code.google.com/p/language-detection/
Copyright (C) 2012 Jörg Prante
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. you may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.