ICU Tokenizeredit

Tokenizes text into words on word boundaries, as defined in UAX #29: Unicode Text Segmentation. It behaves much like the standard tokenizer, but adds better support for some Asian languages by using a dictionary-based approach to identify words in Thai, Lao, Chinese, Japanese, and Korean, and using custom rules to break Myanmar and Khmer text into syllables.

PUT icu_sample
{
  "settings": {
    "index": {
      "analysis": {
        "analyzer": {
          "my_icu_analyzer": {
            "tokenizer": "icu_tokenizer"
          }
        }
      }
    }
  }
}

Rules customizationedit

Warning

This functionality is experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.

You can customize the icu-tokenizer behavior by specifying per-script rule files, see the RBBI rules syntax reference for a more detailed explanation.

To add icu tokenizer rules, set the rule_files settings, which should contain a comma-separated list of code:rulefile pairs in the following format: four-letter ISO 15924 script code, followed by a colon, then a rule file name. Rule files are placed ES_HOME/config directory.

As a demonstration of how the rule files can be used, save the following user file to $ES_HOME/config/KeywordTokenizer.rbbi:

.+ {200};

Then create an analyzer to use this rule file as follows:

PUT icu_sample
{
    "settings": {
        "index":{
            "analysis":{
                "tokenizer" : {
                    "icu_user_file" : {
                       "type" : "icu_tokenizer",
                       "rule_files" : "Latn:KeywordTokenizer.rbbi"
                    }
                },
                "analyzer" : {
                    "my_analyzer" : {
                        "type" : "custom",
                        "tokenizer" : "icu_user_file"
                    }
                }
            }
        }
    }
}

POST icu_sample/_analyze?analyzer=my_analyzer&text=Elasticsearch. Wow!

The above analyze request returns the following:

{
   "tokens": [
      {
         "token": "Elasticsearch. Wow!",
         "start_offset": 0,
         "end_offset": 19,
         "type": "<ALPHANUM>",
         "position": 0
      }
   ]
}