Lithuanian analyzer

The built-in lithuanian analyzer can be applied to a text field using the following command:

  1. PUT /lithuanian-index
  2. {
  3.   "mappings": {
  4.     "properties": {
  5.       "content": {
  6.         "type": "text",
  7.         "analyzer": "lithuanian"
  8.       }
  9.     }
  10.   }
  11. }

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Stem exclusion

You can use stem_exclusion with this language analyzer using the following command:

  1. PUT index_with_stem_exclusion_lithuanian_analyzer
  2. {
  3.   "settings": {
  4.     "analysis": {
  5.       "analyzer": {
  6.         "stem_exclusion_lithuanian_analyzer": {
  7.           "type": "lithuanian",
  8.           "stem_exclusion": ["autoritetas", "patvirtinimas"]
  9.         }
  10.       }
  11.     }
  12.   }
  13. }

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Lithuanian analyzer internals

The lithuanian analyzer is built using the following components:

  • Tokenizer: standard

  • Token filters:

    • lowercase
    • stop (Lithuanian)
    • keyword
    • stemmer (Lithuanian)

Custom Lithuanian analyzer

You can create a custom Lithuanian analyzer using the following command:

  1. PUT /lithuanian-index
  2. {
  3.   "settings": {
  4.     "analysis": {
  5.       "filter": {
  6.         "lithuanian_stop": {
  7.           "type": "stop",
  8.           "stopwords": "_lithuanian_"
  9.         },
  10.         "lithuanian_stemmer": {
  11.           "type": "stemmer",
  12.           "language": "lithuanian"
  13.         },
  14.         "lithuanian_keywords": {
  15.           "type": "keyword_marker",
  16.           "keywords": []
  17.         }
  18.       },
  19.       "analyzer": {
  20.         "lithuanian_analyzer": {
  21.           "type": "custom",
  22.           "tokenizer": "standard",
  23.           "filter": [
  24.             "lowercase",
  25.             "lithuanian_stop",
  26.             "lithuanian_keywords",
  27.             "lithuanian_stemmer"
  28.           ]
  29.         }
  30.       }
  31.     }
  32.   },
  33.   "mappings": {
  34.     "properties": {
  35.       "content": {
  36.         "type": "text",
  37.         "analyzer": "lithuanian_analyzer"
  38.       }
  39.     }
  40.   }
  41. }

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Generated tokens

Use the following request to examine the tokens generated using the analyzer:

  1. POST /lithuanian-index/_analyze
  2. {
  3.   "field": "content",
  4.   "text": "Studentai mokosi Lietuvos universitetuose. Jų numeriai yra 123456."
  5. }

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The response contains the generated tokens:

  1. {
  2.   "tokens": [
  3.     {"token": "student","start_offset": 0,"end_offset": 9,"type": "<ALPHANUM>","position": 0},
  4.     {"token": "mok","start_offset": 10,"end_offset": 16,"type": "<ALPHANUM>","position": 1},
  5.     {"token": "lietuv","start_offset": 17,"end_offset": 25,"type": "<ALPHANUM>","position": 2},
  6.     {"token": "universitet","start_offset": 26,"end_offset": 41,"type": "<ALPHANUM>","position": 3},
  7.     {"token": "num","start_offset": 46,"end_offset": 54,"type": "<ALPHANUM>","position": 5},
  8.     {"token": "123456","start_offset": 59,"end_offset": 65,"type": "<NUM>","position": 7}
  9.   ]
  10. }