[[multi-word-synonyms]] === Multiword Synonyms and Phrase Queries

So far, synonyms appear to be quite straightforward. Unfortunately, this is where things start to go wrong.((("synonyms", "multiword, and phrase queries")))((("phrase matching", "multiword synonyms and"))) For <> to function correctly, Elasticsearch needs to know the position that each term occupies in the original text. Multiword synonyms can play havoc with term positions, especially when the injected synonyms are of differing lengths.

To demonstrate, we'll create a synonym token filter that uses this rule:

"usa,united states,u s a,united states of america"

[source,json]

PUT /my_index { "settings": { "analysis": { "filter": { "my_synonym_filter": { "type": "synonym", "synonyms": [ "usa,united states,u s a,united states of america" ] } }, "analyzer": { "my_synonyms": { "tokenizer": "standard", "filter": [ "lowercase", "my_synonym_filter" ] } } } } }

GET /my_index/_analyze?analyzer=my_synonyms&text=

The United States is wealthy

The tokens emitted by the analyze request look like this:

[source,text]

Pos 1: (the) Pos 2: (usa,united,u,united) Pos 3: (states,s,states) Pos 4: (is,a,of)

Pos 5: (wealthy,america)

If we were to index a document analyzed with synonyms as above, and then run a phrase query without synonyms, we'd have some surprising results. These phrases would not match:

• The usa is wealthy
• The united states of america is wealthy
• The U.S.A. is wealthy

However, these phrases would:

• United states is wealthy
• Usa states of wealthy
• The U.S. of wealthy
• U.S. is america

If we were to use synonyms at query time instead, we would see even more-bizarre matches. Look at the output of this validate-query request:

[source,json]

GET /my_index/_validate/query?explain { "query": { "match_phrase": { "text": { "query": "usa is wealthy", "analyzer": "my_synonyms" } } }

}

The explanation is as follows:

"(usa united u united) (is states s states) (wealthy a of) america"

This would match documents containg u is of america but wouldn't match any document that didn't contain the term america.

[TIP]

Multiword synonyms ((("highlighting searches", "multiword synonyms and")))affect highlighting in a similar way. A query for USA could end up returning a highlighted snippet such as: ``The United States is wealthy''.

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==== Use Simple Contraction for Phrase Queries

The way to avoid this mess is to use <> to inject a single((("synonyms", "multiword, and phrase queries", "using simple contraction")))((("phrase matching", "multiword synonyms and", "using simple contraction")))((("simple contraction (synonyms)", "using for phrase queries"))) term that represents all synonyms, and to use the same synonym token filter at query time:

[source,json]

PUT /my_index { "settings": { "analysis": { "filter": { "my_synonym_filter": { "type": "synonym", "synonyms": [ "united states,u s a,united states of america=>usa" ] } }, "analyzer": { "my_synonyms": { "tokenizer": "standard", "filter": [ "lowercase", "my_synonym_filter" ] } } } } }

GET /my_index/_analyze?analyzer=my_synonyms

The United States is wealthy

The result of the preceding analyze request looks much more sane:

[source,text]

Pos 1: (the) Pos 2: (usa) Pos 3: (is)

Pos 5: (wealthy)

And repeating the validate-query request that we made previously yields a simple, sane explanation:

"usa is wealthy"

The downside of this approach is that, by reducing united states of america down to the single term usa, you can't use the same field to find just the word united or states. You would need to use a separate field with a different analysis chain for that purpose.

==== Synonyms and the query_string Query

We have tried to avoid discussing the query_string query ((("query strings", "synonyms and")))((("synonyms", "multiword, and query string queries")))because we don't recommend using it. In <>, we said that, because the query_string query supports a terse mini search-syntax, it could frequently lead to surprising results or even syntax errors.

One of the gotchas of this query involves multiword synonyms. To support its search-syntax, it has to parse the query string to recognize special operators like AND, OR, +, -, field:, and so forth. (See the full http://bit.ly/151G5I1[`query_string` syntax] here.)

As part of this parsing process, it breaks up the query string on whitespace, and passes each word that it finds to the relevant analyzer separately. This means that your synonym analyzer will never receive a multiword synonym. Instead of seeing United States as a single string, the analyzer will receive United and States separately.

Fortunately, the trustworthy match query supports no such syntax, and multiword synonyms will be passed to the analyzer in their entirety.