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Bengali analyzer

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

PUT /bengali-index
{
  "mappings": {
    "properties": {
      "content": {
        "type": "text",
        "analyzer": "bengali"
      }
    }
  }
}

Stem exclusion

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

PUT index_with_stem_exclusion_bengali_analyzer
{
  "settings": {
    "analysis": {
      "analyzer": {
        "stem_exclusion_bengali_analyzer": {
          "type": "bengali",
          "stem_exclusion": ["কর্তৃপক্ষ", "অনুমোদন"]
        }
      }
    }
  }
}

Bengali analyzer internals

The bengali analyzer is built using the following components:

  • Tokenizer: standard

  • Token filters:

    • lowercase
    • decimal_digit
    • indic_normalization
    • normalization (Bengali)
    • stop (Bengali)
    • keyword
    • stemmer (Bengali)

Custom Bengali analyzer

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

PUT /bengali-index
{
  "settings": {
    "analysis": {
      "filter": {
        "bengali_stop": {
          "type": "stop",
          "stopwords": "_bengali_"
        },
        "bengali_stemmer": {
          "type": "stemmer",
          "language": "bengali"
        },
        "bengali_keywords": {
          "type":       "keyword_marker",
          "keywords":   [] 
        }
      },
      "analyzer": {
        "bengali_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "decimal_digit",
            "indic_normalization",
            "bengali_normalization",
            "bengali_stop",
            "bengali_keywords",
            "bengali_stemmer"
          ]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "content": {
        "type": "text",
        "analyzer": "bengali_analyzer"
      }
    }
  }
}

Generated tokens

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

POST /bengali-index/_analyze
{
  "field": "content",
  "text": "ছাত্ররা বিশ্ববিদ্যালয়ে পড়াশোনা করে। তাদের নম্বরগুলি ১২৩৪৫৬।"
}

The response contains the generated tokens:

{
  "tokens": [
    {"token": "ছাত্র","start_offset": 0,"end_offset": 7,"type": "<ALPHANUM>","position": 0},
    {"token": "বিসসবিদালয়","start_offset": 8,"end_offset": 23,"type": "<ALPHANUM>","position": 1},
    {"token": "পরাসোন","start_offset": 24,"end_offset": 32,"type": "<ALPHANUM>","position": 2},
    {"token": "তা","start_offset": 38,"end_offset": 43,"type": "<ALPHANUM>","position": 4},
    {"token": "নমমর","start_offset": 44,"end_offset": 53,"type": "<ALPHANUM>","position": 5},
    {"token": "123456","start_offset": 54,"end_offset": 60,"type": "<NUM>","position": 6}
  ]
}
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