Latvian analyzer

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

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

copy

Stem exclusion

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

  1. PUT index_with_stem_exclusion_latvian_analyzer
  2. {
  3.   "settings": {
  4.     "analysis": {
  5.       "analyzer": {
  6.         "stem_exclusion_latvian_analyzer": {
  7.           "type": "latvian",
  8.           "stem_exclusion": ["autoritāte", "apstiprinājums"]
  9.         }
  10.       }
  11.     }
  12.   }
  13. }

copy

Latvian analyzer internals

The latvian analyzer is built using the following components:

  • Tokenizer: standard

  • Token filters:

    • lowercase
    • stop (Latvian)
    • keyword
    • stemmer (Latvian)

Custom Latvian analyzer

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

  1. PUT /italian-index
  2. {
  3.   "settings": {
  4.     "analysis": {
  5.       "filter": {
  6.         "italian_stop": {
  7.           "type": "stop",
  8.           "stopwords": "_italian_"
  9.         },
  10.         "italian_elision": {
  11.           "type": "elision",
  12.           "articles": [
  13.                 "c", "l", "all", "dall", "dell",
  14.                 "nell", "sull", "coll", "pell",
  15.                 "gl", "agl", "dagl", "degl", "negl",
  16.                 "sugl", "un", "m", "t", "s", "v", "d"
  17.           ],
  18.           "articles_case": true
  19.         },
  20.         "italian_stemmer": {
  21.           "type": "stemmer",
  22.           "language": "light_italian"
  23.         },
  24.         "italian_keywords": {
  25.           "type": "keyword_marker",
  26.           "keywords": []
  27.         }
  28.       },
  29.       "analyzer": {
  30.         "italian_analyzer": {
  31.           "type": "custom",
  32.           "tokenizer": "standard",
  33.           "filter": [
  34.             "italian_elision",
  35.             "lowercase",
  36.             "italian_stop",
  37.             "italian_keywords",
  38.             "italian_stemmer"
  39.           ]
  40.         }
  41.       }
  42.     }
  43.   },
  44.   "mappings": {
  45.     "properties": {
  46.       "content": {
  47.         "type": "text",
  48.         "analyzer": "italian_analyzer"
  49.       }
  50.     }
  51.   }
  52. }

copy

Generated tokens

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

  1. POST /latvian-index/_analyze
  2. {
  3.   "field": "content",
  4.   "text": "Studenti mācās Latvijas universitātēs. Viņu numuri ir 123456."
  5. }

copy

The response contains the generated tokens:

  1. {
  2.   "tokens": [
  3.     {"token": "student","start_offset": 0,"end_offset": 8,"type": "<ALPHANUM>","position": 0},
  4.     {"token": "māc","start_offset": 9,"end_offset": 14,"type": "<ALPHANUM>","position": 1},
  5.     {"token": "latvij","start_offset": 15,"end_offset": 23,"type": "<ALPHANUM>","position": 2},
  6.     {"token": "universitāt","start_offset": 24,"end_offset": 37,"type": "<ALPHANUM>","position": 3},
  7.     {"token": "vin","start_offset": 39,"end_offset": 43,"type": "<ALPHANUM>","position": 4},
  8.     {"token": "numur","start_offset": 44,"end_offset": 50,"type": "<ALPHANUM>","position": 5},
  9.     {"token": "123456","start_offset": 54,"end_offset": 60,"type": "<NUM>","position": 7}
  10.   ]
  11. }