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| --- | ||
| layout: default | ||
| title: ASCII folding | ||
| parent: Token filters | ||
| nav_order: 20 | ||
| --- | ||
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| # ASCII folding token filter | ||
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| The `asciifolding` token filter converts non-ASCII characters to their closest ASCII equivalents. For example, *é* becomes *e*, *ü* becomes *u*, and *ñ* becomes *n*. This process is known as *transliteration*. | ||
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| The `asciifolding` token filter offers a number of benefits: | ||
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| - **Enhanced search flexibility**: Users often omit accents or special characters when entering queries. The `asciifolding` token filter ensures that such queries still return relevant results. | ||
| - **Normalization**: Standardizes the indexing process by ensuring that accented characters are consistently converted to their ASCII equivalents. | ||
| - **Internationalization**: Particularly useful for applications including multiple languages and character sets. | ||
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| While the `asciifolding` token filter can simplify searches, it may also lead to the loss of specific information, particularly if the distinction between accented and non-accented characters in the dataset is significant. | ||
| {: .warning} | ||
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| ## Parameters | ||
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| You can configure the `asciifolding` token filter using the `preserve_original` parameter. Setting this parameter to `true` keeps both the original token and its ASCII-folded version in the token stream. This can be particularly useful when you want to match both the original (with accents) and the normalized (without accents) versions of a term in a search query. Default is `false`. | ||
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| ## Example | ||
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| The following example request creates a new index named `example_index` and defines an analyzer with the `asciifolding` filter and `preserve_original` parameter set to `true`: | ||
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| ```json | ||
| PUT /example_index | ||
| { | ||
| "settings": { | ||
| "analysis": { | ||
| "filter": { | ||
| "custom_ascii_folding": { | ||
| "type": "asciifolding", | ||
| "preserve_original": true | ||
| } | ||
| }, | ||
| "analyzer": { | ||
| "custom_ascii_analyzer": { | ||
| "type": "custom", | ||
| "tokenizer": "standard", | ||
| "filter": [ | ||
| "lowercase", | ||
| "custom_ascii_folding" | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| ## Generated tokens | ||
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| Use the following request to examine the tokens generated using the analyzer: | ||
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| ```json | ||
| POST /example_index/_analyze | ||
| { | ||
| "analyzer": "custom_ascii_analyzer", | ||
| "text": "Résumé café naïve coördinate" | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The response contains the generated tokens: | ||
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| ```json | ||
| { | ||
| "tokens": [ | ||
| { | ||
| "token": "resume", | ||
| "start_offset": 0, | ||
| "end_offset": 6, | ||
| "type": "<ALPHANUM>", | ||
| "position": 0 | ||
| }, | ||
| { | ||
| "token": "résumé", | ||
| "start_offset": 0, | ||
| "end_offset": 6, | ||
| "type": "<ALPHANUM>", | ||
| "position": 0 | ||
| }, | ||
| { | ||
| "token": "cafe", | ||
| "start_offset": 7, | ||
| "end_offset": 11, | ||
| "type": "<ALPHANUM>", | ||
| "position": 1 | ||
| }, | ||
| { | ||
| "token": "café", | ||
| "start_offset": 7, | ||
| "end_offset": 11, | ||
| "type": "<ALPHANUM>", | ||
| "position": 1 | ||
| }, | ||
| { | ||
| "token": "naive", | ||
| "start_offset": 12, | ||
| "end_offset": 17, | ||
| "type": "<ALPHANUM>", | ||
| "position": 2 | ||
| }, | ||
| { | ||
| "token": "naïve", | ||
| "start_offset": 12, | ||
| "end_offset": 17, | ||
| "type": "<ALPHANUM>", | ||
| "position": 2 | ||
| }, | ||
| { | ||
| "token": "coordinate", | ||
| "start_offset": 18, | ||
| "end_offset": 28, | ||
| "type": "<ALPHANUM>", | ||
| "position": 3 | ||
| }, | ||
| { | ||
| "token": "coördinate", | ||
| "start_offset": 18, | ||
| "end_offset": 28, | ||
| "type": "<ALPHANUM>", | ||
| "position": 3 | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
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