elasticsearch/docs/reference/analysis/tokenizers/letter-tokenizer.asciidoc

[[analysis-letter-tokenizer]]
=== Letter Tokenizer

The `letter` tokenizer breaks text into terms whenever it encounters a
character which is not a letter. It does a reasonable job for most European
languages, but does a terrible job for some Asian languages, where words are
not separated by spaces.

[float]
=== Example output

[source,console]
---------------------------
POST _analyze
{
  "tokenizer": "letter",
  "text": "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone."
}
---------------------------

/////////////////////

[source,console-result]
----------------------------
{
  "tokens": [
    {
      "token": "The",
      "start_offset": 0,
      "end_offset": 3,
      "type": "word",
      "position": 0
    },
    {
      "token": "QUICK",
      "start_offset": 6,
      "end_offset": 11,
      "type": "word",
      "position": 1
    },
    {
      "token": "Brown",
      "start_offset": 12,
      "end_offset": 17,
      "type": "word",
      "position": 2
    },
    {
      "token": "Foxes",
      "start_offset": 18,
      "end_offset": 23,
      "type": "word",
      "position": 3
    },
    {
      "token": "jumped",
      "start_offset": 24,
      "end_offset": 30,
      "type": "word",
      "position": 4
    },
    {
      "token": "over",
      "start_offset": 31,
      "end_offset": 35,
      "type": "word",
      "position": 5
    },
    {
      "token": "the",
      "start_offset": 36,
      "end_offset": 39,
      "type": "word",
      "position": 6
    },
    {
      "token": "lazy",
      "start_offset": 40,
      "end_offset": 44,
      "type": "word",
      "position": 7
    },
    {
      "token": "dog",
      "start_offset": 45,
      "end_offset": 48,
      "type": "word",
      "position": 8
    },
    {
      "token": "s",
      "start_offset": 49,
      "end_offset": 50,
      "type": "word",
      "position": 9
    },
    {
      "token": "bone",
      "start_offset": 51,
      "end_offset": 55,
      "type": "word",
      "position": 10
    }
  ]
}
----------------------------

/////////////////////


The above sentence would produce the following terms:

[source,text]
---------------------------
[ The, QUICK, Brown, Foxes, jumped, over, the, lazy, dog, s, bone ]
---------------------------

[float]
=== Configuration

The `letter` tokenizer is not configurable.