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