[DOCS] Reformat `word_delimiter_graph` token filter (#53170) (#53272)

Makes the following changes to the `word_delimiter_graph` token filter
docs:

* Updates the Lucene experimental admonition.
* Updates description
* Adds analyze snippet
* Adds custom analyzer and custom filter snippets
* Reorganizes and updates parameter list
* Expands and updates section re: differences between `word_delimiter`
  and `word_delimiter_graph`
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<titleabbrev>Word delimiter graph</titleabbrev> <titleabbrev>Word delimiter graph</titleabbrev>
++++ ++++
experimental[This functionality is marked as experimental in Lucene] Splits tokens at non-alphanumeric characters. The `word_delimiter_graph` filter
also performs optional token normalization based on a set of rules. By default,
the filter uses the following rules:
Named `word_delimiter_graph`, it splits words into subwords and performs * Split tokens at non-alphanumeric characters.
optional transformations on subword groups. Words are split into The filter uses these characters as delimiters.
subwords with the following rules: For example: `Super-Duper` -> `Super`, `Duper`
* Remove leading or trailing delimiters from each token.
For example: `XL---42+'Autocoder'` -> `XL`, `42`, `Autocoder`
* Split tokens at letter case transitions.
For example: `PowerShot` -> `Power`, `Shot`
* Split tokens at letter-number transitions.
For example: `XL500` -> `XL`, `500`
* Remove the English possessive (`'s`) from the end of each token.
For example: `Neil's` -> `Neil`
* split on intra-word delimiters (by default, all non alpha-numeric The `word_delimiter_graph` filter uses Lucene's
characters). {lucene-analysis-docs}/miscellaneous/WordDelimiterGraphFilter.html[WordDelimiterGraphFilter].
* "Wi-Fi" -> "Wi", "Fi"
* split on case transitions: "PowerShot" -> "Power", "Shot"
* split on letter-number transitions: "SD500" -> "SD", "500"
* leading and trailing intra-word delimiters on each subword are
ignored: "//hello---there, 'dude'" -> "hello", "there", "dude"
* trailing "'s" are removed for each subword: "O'Neil's" -> "O", "Neil"
Unlike the `word_delimiter`, this token filter correctly handles positions for [TIP]
multi terms expansion at search-time when any of the following options ====
are set to true: The `word_delimiter_graph` filter was designed to remove punctuation from
complex identifiers, such as product IDs or part numbers. For these use cases,
we recommend using the `word_delimiter_graph` filter with the
<<analysis-keyword-tokenizer,`keyword`>> tokenizer.
* `preserve_original` Avoid using the `word_delimiter_graph` filter to split hyphenated words, such as
* `catenate_numbers` `wi-fi`. Because users often search for these words both with and without
* `catenate_words` hyphens, we recommend using the
* `catenate_all` <<analysis-synonym-graph-tokenfilter,`synonym_graph`>> filter instead.
====
Parameters include: [[analysis-word-delimiter-graph-tokenfilter-analyze-ex]]
==== Example
`generate_word_parts`:: The following <<indices-analyze,analyze API>> request uses the
If `true` causes parts of words to be `word_delimiter_graph` filter to split `Neil's Super-Duper-XL500--42+AutoCoder`
generated: "PowerShot" -> "Power" "Shot". Defaults to `true`. into normalized tokens using the filter's default rules:
[source,console]
----
GET /_analyze
{
"tokenizer": "whitespace",
"filter": [ "word_delimiter_graph" ],
"text": "Neil's Super-Duper-XL500--42+AutoCoder"
}
----
The filter produces the following tokens:
[source,txt]
----
[ Neil, Super, Duper, XL, 500, 42, Auto, Coder ]
----
////
[source,console-result]
----
{
"tokens" : [
{
"token" : "Neil",
"start_offset" : 0,
"end_offset" : 4,
"type" : "word",
"position" : 0
},
{
"token" : "Super",
"start_offset" : 7,
"end_offset" : 12,
"type" : "word",
"position" : 1
},
{
"token" : "Duper",
"start_offset" : 13,
"end_offset" : 18,
"type" : "word",
"position" : 2
},
{
"token" : "XL",
"start_offset" : 19,
"end_offset" : 21,
"type" : "word",
"position" : 3
},
{
"token" : "500",
"start_offset" : 21,
"end_offset" : 24,
"type" : "word",
"position" : 4
},
{
"token" : "42",
"start_offset" : 26,
"end_offset" : 28,
"type" : "word",
"position" : 5
},
{
"token" : "Auto",
"start_offset" : 29,
"end_offset" : 33,
"type" : "word",
"position" : 6
},
{
"token" : "Coder",
"start_offset" : 33,
"end_offset" : 38,
"type" : "word",
"position" : 7
}
]
}
----
////
[analysis-word-delimiter-tokenfilter-analyzer-ex]]
==== Add to an analyzer
The following <<indices-create-index,create index API>> request uses the
`word_delimiter_graph` filter to configure a new
<<analysis-custom-analyzer,custom analyzer>>.
[source,console]
----
PUT /my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "whitespace",
"filter": [ "word_delimiter_graph" ]
}
}
}
}
}
----
[WARNING]
====
Avoid using the `word_delimiter_graph` filter with tokenizers that remove
punctuation, such as the <<analysis-standard-tokenizer,`standard`>> tokenizer.
This could prevent the `word_delimiter_graph` filter from splitting tokens
correctly. It can also interfere with the filter's configurable parameters, such
as <<word-delimiter-graph-tokenfilter-catenate-all,`catenate_all`>> or
<<word-delimiter-graph-tokenfilter-preserve-original,`preserve_original`>>. We
recommend using the <<analysis-keyword-tokenizer,`keyword`>> or
<<analysis-whitespace-tokenizer,`whitespace`>> tokenizer instead.
====
[[word-delimiter-graph-tokenfilter-configure-parms]]
==== Configurable parameters
[[word-delimiter-graph-tokenfilter-adjust-offsets]]
`adjust_offsets`::
+
--
(Optional, boolean)
If `true`, the filter adjusts the offsets of split or catenated tokens to better
reflect their actual position in the token stream. Defaults to `true`.
[WARNING]
====
Set `adjust_offsets` to `false` if your analyzer uses filters, such as the
<<analysis-trim-tokenfilter,`trim`>> filter, that change the length of tokens
without changing their offsets. Otherwise, the `word_delimiter_graph` filter
could produce tokens with illegal offsets.
====
--
[[word-delimiter-graph-tokenfilter-catenate-all]]
`catenate_all`::
+
--
(Optional, boolean)
If `true`, the filter produces catenated tokens for chains of alphanumeric
characters separated by non-alphabetic delimiters. For example:
`super-duper-xl-500` -> [**`superduperxl500`**, `super`, `duper`, `xl`, `500` ].
Defaults to `false`.
[WARNING]
====
Setting this parameter to `true` produces multi-position tokens, which are not
supported by indexing.
If this parameter is `true`, avoid using this filter in an index analyzer or
use the <<analysis-flatten-graph-tokenfilter,`flatten_graph`>> filter after
this filter to make the token stream suitable for indexing.
When used for search analysis, catenated tokens can cause problems for the
<<query-dsl-match-query-phrase,`match_phrase`>> query and other queries that
rely on token position for matching. Avoid setting this parameter to `true` if
you plan to use these queries.
====
--
[[word-delimiter-graph-tokenfilter-catenate-numbers]]
`catenate_numbers`::
+
--
(Optional, boolean)
If `true`, the filter produces catenated tokens for chains of numeric characters
separated by non-alphabetic delimiters. For example: `01-02-03` ->
[**`010203`**, `01`, `02`, `03` ]. Defaults to `false`.
[WARNING]
====
Setting this parameter to `true` produces multi-position tokens, which are not
supported by indexing.
If this parameter is `true`, avoid using this filter in an index analyzer or
use the <<analysis-flatten-graph-tokenfilter,`flatten_graph`>> filter after
this filter to make the token stream suitable for indexing.
When used for search analysis, catenated tokens can cause problems for the
<<query-dsl-match-query-phrase,`match_phrase`>> query and other queries that
rely on token position for matching. Avoid setting this parameter to `true` if
you plan to use these queries.
====
--
[[word-delimiter-graph-tokenfilter-catenate-words]]
`catenate_words`::
+
--
(Optional, boolean)
If `true`, the filter produces catenated tokens for chains of alphabetical
characters separated by non-alphabetic delimiters. For example: `super-duper-xl`
-> [**`superduperxl`**, `super`, `duper`, `xl`]. Defaults to `false`.
[WARNING]
====
Setting this parameter to `true` produces multi-position tokens, which are not
supported by indexing.
If this parameter is `true`, avoid using this filter in an index analyzer or
use the <<analysis-flatten-graph-tokenfilter,`flatten_graph`>> filter after
this filter to make the token stream suitable for indexing.
When used for search analysis, catenated tokens can cause problems for the
<<query-dsl-match-query-phrase,`match_phrase`>> query and other queries that
rely on token position for matching. Avoid setting this parameter to `true` if
you plan to use these queries.
====
--
`generate_number_parts`:: `generate_number_parts`::
If `true` causes number subwords to be (Optional, boolean)
generated: "500-42" -> "500" "42". Defaults to `true`. If `true`, the filter includes tokens consisting of only numeric characters in
the output. If `false`, the filter excludes these tokens from the output.
Defaults to `true`.
`catenate_words`:: `generate_word_parts`::
If `true` causes maximum runs of word parts to be (Optional, boolean)
catenated: "wi-fi" -> "wifi". Defaults to `false`. If `true`, the filter includes tokens consisting of only alphabetical characters
in the output. If `false`, the filter excludes these tokens from the output.
`catenate_numbers`:: Defaults to `true`.
If `true` causes maximum runs of number parts to
be catenated: "500-42" -> "50042". Defaults to `false`.
`catenate_all`::
If `true` causes all subword parts to be catenated:
"wi-fi-4000" -> "wifi4000". Defaults to `false`.
`split_on_case_change`::
If `true` causes "PowerShot" to be two tokens;
("Power-Shot" remains two parts regards). Defaults to `true`.
[[word-delimiter-graph-tokenfilter-preserve-original]]
`preserve_original`:: `preserve_original`::
If `true` includes original words in subwords: +
"500-42" -> "500-42" "500" "42". Defaults to `false`. --
(Optional, boolean)
If `true`, the filter includes the original version of any split tokens in the
output. This original version includes non-alphanumeric delimiters. For example:
`super-duper-xl-500` -> [**`super-duper-xl-500`**, `super`, `duper`, `xl`, `500`
]. Defaults to `false`.
`split_on_numerics`:: [WARNING]
If `true` causes "j2se" to be three tokens; "j" ====
"2" "se". Defaults to `true`. Setting this parameter to `true` produces multi-position tokens, which are not
supported by indexing.
`stem_english_possessive`:: If this parameter is `true`, avoid using this filter in an index analyzer or
If `true` causes trailing "'s" to be use the <<analysis-flatten-graph-tokenfilter,`flatten_graph`>> filter after
removed for each subword: "O'Neil's" -> "O", "Neil". Defaults to `true`. this filter to make the token stream suitable for indexing.
====
Advance settings include: --
`protected_words`:: `protected_words`::
A list of protected words from being delimiter. (Optional, array of strings)
Either an array, or also can set `protected_words_path` which resolved Array of tokens the filter won't split.
to a file configured with protected words (one on each line).
Automatically resolves to `config/` based location if exists.
`adjust_offsets`:: `protected_words_path`::
By default, the filter tries to output subtokens with adjusted offsets +
to reflect their actual position in the token stream. However, when --
used in combination with other filters that alter the length or starting (Optional, string)
position of tokens without changing their offsets Path to a file that contains a list of tokens the filter won't split.
(e.g. <<analysis-trim-tokenfilter,`trim`>>) this can cause tokens with
illegal offsets to be emitted. Setting `adjust_offsets` to false will This path must be absolute or relative to the `config` location, and the file
stop `word_delimiter_graph` from adjusting these internal offsets. must be UTF-8 encoded. Each token in the file must be separated by a line
break.
--
`split_on_case_change`::
(Optional, boolean)
If `true`, the filter splits tokens at letter case transitions. For example:
`camelCase` -> [ `camel`, `Case`]. Defaults to `true`.
`split_on_numerics`::
(Optional, boolean)
If `true`, the filter splits tokens at letter-number transitions. For example:
`j2se` -> [ `j`, `2`, `se` ]. Defaults to `true`.
`stem_english_possessive`::
(Optional, boolean)
If `true`, the filter removes the English possessive (`'s`) from the end of each
token. For example: `O'Neil's` -> `[ `O`, `Neil` ]. Defaults to `true`.
`type_table`:: `type_table`::
A custom type mapping table, for example (when configured +
using `type_table_path`): --
(Optional, array of strings)
Array of custom type mappings for characters. This allows you to map
non-alphanumeric characters as numeric or alphanumeric to avoid splitting on
those characters.
[source,type_table] For example, the following array maps the plus (`+`) and hyphen (`-`) characters
-------------------------------------------------- as alphanumeric, which means they won't be treated as delimiters:
# Map the $, %, '.', and ',' characters to DIGIT
# This might be useful for financial data.
$ => DIGIT
% => DIGIT
. => DIGIT
\\u002C => DIGIT
# in some cases you might not want to split on ZWJ `["+ => ALPHA", "- => ALPHA"]`
# this also tests the case where we need a bigger byte[]
# see http://en.wikipedia.org/wiki/Zero-width_joiner
\\u200D => ALPHANUM
--------------------------------------------------
NOTE: Using a tokenizer like the `standard` tokenizer may interfere with Supported types include:
the `catenate_*` and `preserve_original` parameters, as the original
string may already have lost punctuation during tokenization. Instead, * `ALPHA` (Alphabetical)
you may want to use the `whitespace` tokenizer. * `ALPHANUM` (Alphanumeric)
* `DIGIT` (Numeric)
* `LOWER` (Lowercase alphabetical)
* `SUBWORD_DELIM` (Non-alphanumeric delimiter)
* `UPPER` (Uppercase alphabetical)
--
`type_table_path`::
+
--
(Optional, string)
Path to a file that contains custom type mappings for characters. This allows
you to map non-alphanumeric characters as numeric or alphanumeric to avoid
splitting on those characters.
For example, the contents of this file may contain the following:
[source,txt]
----
# Map the $, %, '.', and ',' characters to DIGIT
# This might be useful for financial data.
$ => DIGIT
% => DIGIT
. => DIGIT
\\u002C => DIGIT
# in some cases you might not want to split on ZWJ
# this also tests the case where we need a bigger byte[]
# see http://en.wikipedia.org/wiki/Zero-width_joiner
\\u200D => ALPHANUM
----
Supported types include:
* `ALPHA` (Alphabetical)
* `ALPHANUM` (Alphanumeric)
* `DIGIT` (Numeric)
* `LOWER` (Lowercase alphabetical)
* `SUBWORD_DELIM` (Non-alphanumeric delimiter)
* `UPPER` (Uppercase alphabetical)
This file path must be absolute or relative to the `config` location, and the
file must be UTF-8 encoded. Each mapping in the file must be separated by a line
break.
--
[[analysis-word-delimiter-graph-tokenfilter-customize]]
==== Customize
To customize the `word_delimiter_graph` filter, duplicate it to create the basis
for a new custom token filter. You can modify the filter using its configurable
parameters.
For example, the following request creates a `word_delimiter_graph`
filter that uses the following rules:
* Split tokens at non-alphanumeric characters, _except_ the hyphen (`-`)
character.
* Remove leading or trailing delimiters from each token.
* Do _not_ split tokens at letter case transitions.
* Do _not_ split tokens at letter-number transitions.
* Remove the English possessive (`'s`) from the end of each token.
[source,console]
----
PUT /my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "whitespace",
"filter": [ "my_custom_word_delimiter_graph_filter" ]
}
},
"filter": {
"my_custom_word_delimiter_graph_filter": {
"type": "word_delimiter_graph",
"type_table": [ "- => ALPHA" ],
"split_on_case_change": false,
"split_on_numerics": false,
"stem_english_possessive": true
}
}
}
}
}
----
[[analysis-word-delimiter-graph-differences]]
==== Differences between `word_delimiter_graph` and `word_delimiter`
Both the `word_delimiter_graph` and
<<analysis-word-delimiter-tokenfilter,`word_delimiter`>> filters produce tokens
that span multiple positions when any of the following parameters are `true`:
* <<word-delimiter-graph-tokenfilter-catenate-all,`catenate_all`>>
* <<word-delimiter-graph-tokenfilter-catenate-numbers,`catenate_numbers`>>
* <<word-delimiter-graph-tokenfilter-catenate-words,`catenate_words`>>
* <<word-delimiter-graph-tokenfilter-preserve-original,`preserve_original`>>
However, only the `word_delimiter_graph` filter assigns multi-position tokens a
`positionLength` attribute, which indicates the number of positions a token
spans. This ensures the `word_delimiter_graph` filter always produces valid token
https://en.wikipedia.org/wiki/Directed_acyclic_graph[graphs].
The `word_delimiter` filter does not assign multi-position tokens a
`positionLength` attribute. This means it produces invalid graphs for streams
including these tokens.
While indexing does not support token graphs containing multi-position tokens,
queries, such as the <<query-dsl-match-query-phrase,`match_phrase`>> query, can
use these graphs to generate multiple sub-queries from a single query string.
To see how token graphs produced by the `word_delimiter` and
`word_delimiter_graph` filters differ, check out the following example.
.*Example*
[%collapsible]
====
[[analysis-word-delimiter-graph-basic-token-graph]]
*Basic token graph*
Both the `word_delimiter` and `word_delimiter_graph` produce the following token
graph for `PowerShot2000` when the following parameters are `false`:
* <<word-delimiter-graph-tokenfilter-catenate-all,`catenate_all`>>
* <<word-delimiter-graph-tokenfilter-catenate-numbers,`catenate_numbers`>>
* <<word-delimiter-graph-tokenfilter-catenate-words,`catenate_words`>>
* <<word-delimiter-graph-tokenfilter-preserve-original,`preserve_original`>>
This graph does not contain multi-position tokens. All tokens span only one
position.
image::images/analysis/token-graph-basic.svg[align="center"]
[[analysis-word-delimiter-graph-wdg-token-graph]]
*`word_delimiter_graph` graph with a multi-position token*
The `word_delimiter_graph` filter produces the following token graph for
`PowerShot2000` when `catenate_words` is `true`.
This graph correctly indicates the catenated `PowerShot` token spans two
positions.
image::images/analysis/token-graph-wdg.svg[align="center"]
[[analysis-word-delimiter-graph-wd-token-graph]]
*`word_delimiter` graph with a multi-position token*
When `catenate_words` is `true`, the `word_delimiter` filter produces
the following token graph for `PowerShot2000`.
Note that the catenated `PowerShot` token should span two positions but only
spans one in the token graph, making it invalid.
image::images/analysis/token-graph-wd.svg[align="center"]
====

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