5.3.2 You Have an Accent
English uses diacritics (like ´
, ^
, and ¨
) only for imported words—like rôle
, déjà
, and däis
—but usually they are optional. Other languages require diacritics in order to be correct. Of course, just because words are spelled correctly in your index doesn’t mean that the user will search for the correct spelling.
It is often useful to strip diacritics from words, allowing rôle
to match role
, and vice versa. With Western languages, this can be done with the asciifolding
character filter. Actually, it does more than just strip diacritics. It tries to convert many Unicode characters into a simpler ASCII representation:
ß ⇒ ss
æ ⇒ ae
ł ⇒ l
ɰ ⇒ m
⁇ ⇒ ??
❷ ⇒ 2
⁶ ⇒ 6
Like the lowercase
filter, the asciifolding
filter doesn’t require any configuration but can be included directly in a custom
analyzer:
PUT /my_index
{
"settings": {
"analysis": {
"analyzer": {
"folding": {
"tokenizer": "standard",
"filter": [ "lowercase", "asciifolding" ]
}
}
}
}
}
GET /my_index?analyzer=folding
My œsophagus caused a débâcle ①
① Emits my
, oesophagus
, caused
, a
, debacle
Retaining Meaning
Of course, when you strip diacritical marks from a word, you lose meaning. For instance, consider these three Spanish words:
esta
Feminine form of the adjective this, as in esta silla (this chair) or esta (this one).
ésta
An archaic form of esta.
está
The third-person form of the verb estar (to be), as in está feliz (he is happy).
While we would like to conflate the first two forms, they differ in meaning from the third form, which we would like to keep separate. Similarly:
sé
The first person form of the verb saber (to know) as in Yo sé (I know).
se
The third-person reflexive pronoun used with many verbs, such as se sabe (it is known).
Unfortunately, there is no easy way to separate words that should have their diacritics removed from words that shouldn’t. And it is quite likely that your users won’t know either.
Instead, we index the text twice: once in the original form and once with diacritics removed:
PUT /my_index/_mapping/my_type
{
"properties": {
"title": { ①
"type": "string",
"analyzer": "standard",
"fields": {
"folded": { ②
"type": "string",
"analyzer": "folding"
}
}
}
}
}
① The title field uses the standard analyzer and will contain the original word with diacritics in place.
② The title.folded field uses the folding analyzer, which strips the diacritical marks.
You can test the field mappings by using the analyze
API on the sentence Esta está loca (This woman is crazy):
GET /my_index/_analyze?field=title ①
Esta está loca
GET /my_index/_analyze?field=title.folded ②
Esta está loca
① Emits esta
, está
, loca
② Emits esta
, esta
, loca
Let’s index some documents to test it out:
PUT /my_index/my_type/1
{ "title": "Esta loca!" }
PUT /my_index/my_type/2
{ "title": "Está loca!" }
Now we can search across both fields, using the multi_match
query in most_fields
mode to combine the scores from each field:
GET /my_index/_search
{
"query": {
"multi_match": {
"type": "most_fields",
"query": "esta loca",
"fields": [ "title", "title.folded" ]
}
}
}
Running this query through the validate-query
API helps to explain how the query is executed:
GET /my_index/_validate/query?explain
{
"query": {
"multi_match": {
"type": "most_fields",
"query": "está loca",
"fields": [ "title", "title.folded" ]
}
}
}
The multi-match
query searches for the original form of the word (está
) in the title
field, and the form without diacritics esta
in the title.folded
field:
(title:está title:loca ) (title.folded:esta title.folded:loca)
It doesn’t matter whether the user searches for esta
or está
; both documents will match because the form without diacritics exists in the the title.folded
field. However, only the original form exists in the title
field. This extra match will push the document containing the original form of the word to the top of the results list.
We use the title.folded
field to widen the net in order to match more documents, and use the original title
field to push the most relevant document to the top. This same technique can be used wherever an analyzer is used, to increase matches at the expense of meaning.
Tip
The
asciifolding
filter does have an option calledpreserve_original
that allows you to index the original token and the folded token in the same position in the same field. With this option enabled, you would end up with something like this:Position 1 Position 2 ------------------------- (ésta,esta) loca -------------------------While this appears to be a nice way to save space, it does mean that you have no way of saying, “Give me an exact match on the original word.” Mixing tokens with and without diacritics can also end up interfering with term-frequency counts, resulting in less-reliable relevance calcuations.
As a rule, it is cleaner to index each field variant into a separate field, as we have done in this section.