OpenSearch/docs/reference/analysis/tokenizers/standard-tokenizer.asciidoc

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[[analysis-standard-tokenizer]]
=== Standard tokenizer
++++
<titleabbrev>Standard</titleabbrev>
++++
The `standard` tokenizer provides grammar based tokenization (based on the
Unicode Text Segmentation algorithm, as specified in
https://unicode.org/reports/tr29/[Unicode Standard Annex #29]) and works well
for most languages.
[discrete]
=== Example output
[source,console]
---------------------------
POST _analyze
{
"tokenizer": "standard",
"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": "<ALPHANUM>",
"position": 0
},
{
"token": "2",
"start_offset": 4,
"end_offset": 5,
"type": "<NUM>",
"position": 1
},
{
"token": "QUICK",
"start_offset": 6,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "Brown",
"start_offset": 12,
"end_offset": 17,
"type": "<ALPHANUM>",
"position": 3
},
{
"token": "Foxes",
"start_offset": 18,
"end_offset": 23,
"type": "<ALPHANUM>",
"position": 4
},
{
"token": "jumped",
"start_offset": 24,
"end_offset": 30,
"type": "<ALPHANUM>",
"position": 5
},
{
"token": "over",
"start_offset": 31,
"end_offset": 35,
"type": "<ALPHANUM>",
"position": 6
},
{
"token": "the",
"start_offset": 36,
"end_offset": 39,
"type": "<ALPHANUM>",
"position": 7
},
{
"token": "lazy",
"start_offset": 40,
"end_offset": 44,
"type": "<ALPHANUM>",
"position": 8
},
{
"token": "dog's",
"start_offset": 45,
"end_offset": 50,
"type": "<ALPHANUM>",
"position": 9
},
{
"token": "bone",
"start_offset": 51,
"end_offset": 55,
"type": "<ALPHANUM>",
"position": 10
}
]
}
----------------------------
/////////////////////
The above sentence would produce the following terms:
[source,text]
---------------------------
[ The, 2, QUICK, Brown, Foxes, jumped, over, the, lazy, dog's, bone ]
---------------------------
[discrete]
=== Configuration
The `standard` tokenizer accepts the following parameters:
[horizontal]
`max_token_length`::
The maximum token length. If a token is seen that exceeds this length then
it is split at `max_token_length` intervals. Defaults to `255`.
[discrete]
=== Example configuration
In this example, we configure the `standard` tokenizer to have a
`max_token_length` of 5 (for demonstration purposes):
[source,console]
----------------------------
PUT my-index-000001
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "standard",
"max_token_length": 5
}
}
}
}
}
POST my-index-000001/_analyze
{
"analyzer": "my_analyzer",
"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": "<ALPHANUM>",
"position": 0
},
{
"token": "2",
"start_offset": 4,
"end_offset": 5,
"type": "<NUM>",
"position": 1
},
{
"token": "QUICK",
"start_offset": 6,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 2
},
{
"token": "Brown",
"start_offset": 12,
"end_offset": 17,
"type": "<ALPHANUM>",
"position": 3
},
{
"token": "Foxes",
"start_offset": 18,
"end_offset": 23,
"type": "<ALPHANUM>",
"position": 4
},
{
"token": "jumpe",
"start_offset": 24,
"end_offset": 29,
"type": "<ALPHANUM>",
"position": 5
},
{
"token": "d",
"start_offset": 29,
"end_offset": 30,
"type": "<ALPHANUM>",
"position": 6
},
{
"token": "over",
"start_offset": 31,
"end_offset": 35,
"type": "<ALPHANUM>",
"position": 7
},
{
"token": "the",
"start_offset": 36,
"end_offset": 39,
"type": "<ALPHANUM>",
"position": 8
},
{
"token": "lazy",
"start_offset": 40,
"end_offset": 44,
"type": "<ALPHANUM>",
"position": 9
},
{
"token": "dog's",
"start_offset": 45,
"end_offset": 50,
"type": "<ALPHANUM>",
"position": 10
},
{
"token": "bone",
"start_offset": 51,
"end_offset": 55,
"type": "<ALPHANUM>",
"position": 11
}
]
}
----------------------------
/////////////////////
The above example produces the following terms:
[source,text]
---------------------------
[ The, 2, QUICK, Brown, Foxes, jumpe, d, over, the, lazy, dog's, bone ]
---------------------------