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<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /><title>12.6. Dictionaries</title><link rel="stylesheet" type="text/css" href="stylesheet.css" /><link rev="made" href="pgsql-docs@lists.postgresql.org" /><meta name="generator" content="DocBook XSL Stylesheets Vsnapshot" /><link rel="prev" href="textsearch-parsers.html" title="12.5. Parsers" /><link rel="next" href="textsearch-configuration.html" title="12.7. Configuration Example" /></head><body id="docContent" class="container-fluid col-10"><div xmlns="http://www.w3.org/TR/xhtml1/transitional" class="navheader"><table width="100%" summary="Navigation header"><tr><th colspan="5" align="center">12.6. Dictionaries</th></tr><tr><td width="10%" align="left"><a accesskey="p" href="textsearch-parsers.html" title="12.5. Parsers">Prev</a> </td><td width="10%" align="left"><a accesskey="u" href="textsearch.html" title="Chapter 12. Full Text Search">Up</a></td><th width="60%" align="center">Chapter 12. Full Text Search</th><td width="10%" align="right"><a accesskey="h" href="index.html" title="PostgreSQL 14.5 Documentation">Home</a></td><td width="10%" align="right"> <a accesskey="n" href="textsearch-configuration.html" title="12.7. Configuration Example">Next</a></td></tr></table><hr></hr></div><div class="sect1" id="TEXTSEARCH-DICTIONARIES"><div class="titlepage"><div><div><h2 class="title" style="clear: both">12.6. Dictionaries</h2></div></div></div><div class="toc"><dl class="toc"><dt><span class="sect2"><a href="textsearch-dictionaries.html#TEXTSEARCH-STOPWORDS">12.6.1. Stop Words</a></span></dt><dt><span class="sect2"><a href="textsearch-dictionaries.html#TEXTSEARCH-SIMPLE-DICTIONARY">12.6.2. Simple Dictionary</a></span></dt><dt><span class="sect2"><a href="textsearch-dictionaries.html#TEXTSEARCH-SYNONYM-DICTIONARY">12.6.3. Synonym Dictionary</a></span></dt><dt><span class="sect2"><a href="textsearch-dictionaries.html#TEXTSEARCH-THESAURUS">12.6.4. Thesaurus Dictionary</a></span></dt><dt><span class="sect2"><a href="textsearch-dictionaries.html#TEXTSEARCH-ISPELL-DICTIONARY">12.6.5. <span class="application">Ispell</span> Dictionary</a></span></dt><dt><span class="sect2"><a href="textsearch-dictionaries.html#TEXTSEARCH-SNOWBALL-DICTIONARY">12.6.6. <span class="application">Snowball</span> Dictionary</a></span></dt></dl></div><p>
Dictionaries are used to eliminate words that should not be considered in a
search (<em class="firstterm">stop words</em>), and to <em class="firstterm">normalize</em> words so
that different derived forms of the same word will match. A successfully
normalized word is called a <em class="firstterm">lexeme</em>. Aside from
improving search quality, normalization and removal of stop words reduce the
size of the <code class="type">tsvector</code> representation of a document, thereby
improving performance. Normalization does not always have linguistic meaning
and usually depends on application semantics.
</p><p>
Some examples of normalization:
</p><div class="itemizedlist"><ul class="itemizedlist compact" style="list-style-type: bullet; "><li class="listitem" style="list-style-type: disc"><p>
Linguistic — Ispell dictionaries try to reduce input words to a
normalized form; stemmer dictionaries remove word endings
</p></li><li class="listitem" style="list-style-type: disc"><p>
<acronym class="acronym">URL</acronym> locations can be canonicalized to make
equivalent URLs match:
</p><div class="itemizedlist"><ul class="itemizedlist compact" style="list-style-type: bullet; "><li class="listitem" style="list-style-type: disc"><p>
http://www.pgsql.ru/db/mw/index.html
</p></li><li class="listitem" style="list-style-type: disc"><p>
http://www.pgsql.ru/db/mw/
</p></li><li class="listitem" style="list-style-type: disc"><p>
http://www.pgsql.ru/db/../db/mw/index.html
</p></li></ul></div><p>
</p></li><li class="listitem" style="list-style-type: disc"><p>
Color names can be replaced by their hexadecimal values, e.g.,
<code class="literal">red, green, blue, magenta -> FF0000, 00FF00, 0000FF, FF00FF</code>
</p></li><li class="listitem" style="list-style-type: disc"><p>
If indexing numbers, we can
remove some fractional digits to reduce the range of possible
numbers, so for example <span class="emphasis"><em>3.14</em></span>159265359,
<span class="emphasis"><em>3.14</em></span>15926, <span class="emphasis"><em>3.14</em></span> will be the same
after normalization if only two digits are kept after the decimal point.
</p></li></ul></div><p>
</p><p>
A dictionary is a program that accepts a token as
input and returns:
</p><div class="itemizedlist"><ul class="itemizedlist compact" style="list-style-type: bullet; "><li class="listitem" style="list-style-type: disc"><p>
an array of lexemes if the input token is known to the dictionary
(notice that one token can produce more than one lexeme)
</p></li><li class="listitem" style="list-style-type: disc"><p>
a single lexeme with the <code class="literal">TSL_FILTER</code> flag set, to replace
the original token with a new token to be passed to subsequent
dictionaries (a dictionary that does this is called a
<em class="firstterm">filtering dictionary</em>)
</p></li><li class="listitem" style="list-style-type: disc"><p>
an empty array if the dictionary knows the token, but it is a stop word
</p></li><li class="listitem" style="list-style-type: disc"><p>
<code class="literal">NULL</code> if the dictionary does not recognize the input token
</p></li></ul></div><p>
</p><p>
<span class="productname">PostgreSQL</span> provides predefined dictionaries for
many languages. There are also several predefined templates that can be
used to create new dictionaries with custom parameters. Each predefined
dictionary template is described below. If no existing
template is suitable, it is possible to create new ones; see the
<code class="filename">contrib/</code> area of the <span class="productname">PostgreSQL</span> distribution
for examples.
</p><p>
A text search configuration binds a parser together with a set of
dictionaries to process the parser's output tokens. For each token
type that the parser can return, a separate list of dictionaries is
specified by the configuration. When a token of that type is found
by the parser, each dictionary in the list is consulted in turn,
until some dictionary recognizes it as a known word. If it is identified
as a stop word, or if no dictionary recognizes the token, it will be
discarded and not indexed or searched for.
Normally, the first dictionary that returns a non-<code class="literal">NULL</code>
output determines the result, and any remaining dictionaries are not
consulted; but a filtering dictionary can replace the given word
with a modified word, which is then passed to subsequent dictionaries.
</p><p>
The general rule for configuring a list of dictionaries
is to place first the most narrow, most specific dictionary, then the more
general dictionaries, finishing with a very general dictionary, like
a <span class="application">Snowball</span> stemmer or <code class="literal">simple</code>, which
recognizes everything. For example, for an astronomy-specific search
(<code class="literal">astro_en</code> configuration) one could bind token type
<code class="type">asciiword</code> (ASCII word) to a synonym dictionary of astronomical
terms, a general English dictionary and a <span class="application">Snowball</span> English
stemmer:
</p><pre class="programlisting">
ALTER TEXT SEARCH CONFIGURATION astro_en
ADD MAPPING FOR asciiword WITH astrosyn, english_ispell, english_stem;
</pre><p>
</p><p>
A filtering dictionary can be placed anywhere in the list, except at the
end where it'd be useless. Filtering dictionaries are useful to partially
normalize words to simplify the task of later dictionaries. For example,
a filtering dictionary could be used to remove accents from accented
letters, as is done by the <a class="xref" href="unaccent.html" title="F.45. unaccent">unaccent</a> module.
</p><div class="sect2" id="TEXTSEARCH-STOPWORDS"><div class="titlepage"><div><div><h3 class="title">12.6.1. Stop Words</h3></div></div></div><p>
Stop words are words that are very common, appear in almost every
document, and have no discrimination value. Therefore, they can be ignored
in the context of full text searching. For example, every English text
contains words like <code class="literal">a</code> and <code class="literal">the</code>, so it is
useless to store them in an index. However, stop words do affect the
positions in <code class="type">tsvector</code>, which in turn affect ranking:
</p><pre class="screen">
SELECT to_tsvector('english', 'in the list of stop words');
to_tsvector
----------------------------
'list':3 'stop':5 'word':6
</pre><p>
The missing positions 1,2,4 are because of stop words. Ranks
calculated for documents with and without stop words are quite different:
</p><pre class="screen">
SELECT ts_rank_cd (to_tsvector('english', 'in the list of stop words'), to_tsquery('list & stop'));
ts_rank_cd
------------
0.05
SELECT ts_rank_cd (to_tsvector('english', 'list stop words'), to_tsquery('list & stop'));
ts_rank_cd
------------
0.1
</pre><p>
</p><p>
It is up to the specific dictionary how it treats stop words. For example,
<code class="literal">ispell</code> dictionaries first normalize words and then
look at the list of stop words, while <code class="literal">Snowball</code> stemmers
first check the list of stop words. The reason for the different
behavior is an attempt to decrease noise.
</p></div><div class="sect2" id="TEXTSEARCH-SIMPLE-DICTIONARY"><div class="titlepage"><div><div><h3 class="title">12.6.2. Simple Dictionary</h3></div></div></div><p>
The <code class="literal">simple</code> dictionary template operates by converting the
input token to lower case and checking it against a file of stop words.
If it is found in the file then an empty array is returned, causing
the token to be discarded. If not, the lower-cased form of the word
is returned as the normalized lexeme. Alternatively, the dictionary
can be configured to report non-stop-words as unrecognized, allowing
them to be passed on to the next dictionary in the list.
</p><p>
Here is an example of a dictionary definition using the <code class="literal">simple</code>
template:
</p><pre class="programlisting">
CREATE TEXT SEARCH DICTIONARY public.simple_dict (
TEMPLATE = pg_catalog.simple,
STOPWORDS = english
);
</pre><p>
Here, <code class="literal">english</code> is the base name of a file of stop words.
The file's full name will be
<code class="filename">$SHAREDIR/tsearch_data/english.stop</code>,
where <code class="literal">$SHAREDIR</code> means the
<span class="productname">PostgreSQL</span> installation's shared-data directory,
often <code class="filename">/usr/local/share/postgresql</code> (use <code class="command">pg_config
--sharedir</code> to determine it if you're not sure).
The file format is simply a list
of words, one per line. Blank lines and trailing spaces are ignored,
and upper case is folded to lower case, but no other processing is done
on the file contents.
</p><p>
Now we can test our dictionary:
</p><pre class="screen">
SELECT ts_lexize('public.simple_dict', 'YeS');
ts_lexize
-----------
{yes}
SELECT ts_lexize('public.simple_dict', 'The');
ts_lexize
-----------
{}
</pre><p>
</p><p>
We can also choose to return <code class="literal">NULL</code>, instead of the lower-cased
word, if it is not found in the stop words file. This behavior is
selected by setting the dictionary's <code class="literal">Accept</code> parameter to
<code class="literal">false</code>. Continuing the example:
</p><pre class="screen">
ALTER TEXT SEARCH DICTIONARY public.simple_dict ( Accept = false );
SELECT ts_lexize('public.simple_dict', 'YeS');
ts_lexize
-----------
SELECT ts_lexize('public.simple_dict', 'The');
ts_lexize
-----------
{}
</pre><p>
</p><p>
With the default setting of <code class="literal">Accept</code> = <code class="literal">true</code>,
it is only useful to place a <code class="literal">simple</code> dictionary at the end
of a list of dictionaries, since it will never pass on any token to
a following dictionary. Conversely, <code class="literal">Accept</code> = <code class="literal">false</code>
is only useful when there is at least one following dictionary.
</p><div class="caution"><h3 class="title">Caution</h3><p>
Most types of dictionaries rely on configuration files, such as files of
stop words. These files <span class="emphasis"><em>must</em></span> be stored in UTF-8 encoding.
They will be translated to the actual database encoding, if that is
different, when they are read into the server.
</p></div><div class="caution"><h3 class="title">Caution</h3><p>
Normally, a database session will read a dictionary configuration file
only once, when it is first used within the session. If you modify a
configuration file and want to force existing sessions to pick up the
new contents, issue an <code class="command">ALTER TEXT SEARCH DICTIONARY</code> command
on the dictionary. This can be a <span class="quote">“<span class="quote">dummy</span>”</span> update that doesn't
actually change any parameter values.
</p></div></div><div class="sect2" id="TEXTSEARCH-SYNONYM-DICTIONARY"><div class="titlepage"><div><div><h3 class="title">12.6.3. Synonym Dictionary</h3></div></div></div><p>
This dictionary template is used to create dictionaries that replace a
word with a synonym. Phrases are not supported (use the thesaurus
template (<a class="xref" href="textsearch-dictionaries.html#TEXTSEARCH-THESAURUS" title="12.6.4. Thesaurus Dictionary">Section 12.6.4</a>) for that). A synonym
dictionary can be used to overcome linguistic problems, for example, to
prevent an English stemmer dictionary from reducing the word <span class="quote">“<span class="quote">Paris</span>”</span> to
<span class="quote">“<span class="quote">pari</span>”</span>. It is enough to have a <code class="literal">Paris paris</code> line in the
synonym dictionary and put it before the <code class="literal">english_stem</code>
dictionary. For example:
</p><pre class="screen">
SELECT * FROM ts_debug('english', 'Paris');
alias | description | token | dictionaries | dictionary | lexemes
-----------+-----------------+-------+----------------+--------------+---------
asciiword | Word, all ASCII | Paris | {english_stem} | english_stem | {pari}
CREATE TEXT SEARCH DICTIONARY my_synonym (
TEMPLATE = synonym,
SYNONYMS = my_synonyms
);
ALTER TEXT SEARCH CONFIGURATION english
ALTER MAPPING FOR asciiword
WITH my_synonym, english_stem;
SELECT * FROM ts_debug('english', 'Paris');
alias | description | token | dictionaries | dictionary | lexemes
-----------+-----------------+-------+---------------------------+------------+---------
asciiword | Word, all ASCII | Paris | {my_synonym,english_stem} | my_synonym | {paris}
</pre><p>
</p><p>
The only parameter required by the <code class="literal">synonym</code> template is
<code class="literal">SYNONYMS</code>, which is the base name of its configuration file
— <code class="literal">my_synonyms</code> in the above example.
The file's full name will be
<code class="filename">$SHAREDIR/tsearch_data/my_synonyms.syn</code>
(where <code class="literal">$SHAREDIR</code> means the
<span class="productname">PostgreSQL</span> installation's shared-data directory).
The file format is just one line
per word to be substituted, with the word followed by its synonym,
separated by white space. Blank lines and trailing spaces are ignored.
</p><p>
The <code class="literal">synonym</code> template also has an optional parameter
<code class="literal">CaseSensitive</code>, which defaults to <code class="literal">false</code>. When
<code class="literal">CaseSensitive</code> is <code class="literal">false</code>, words in the synonym file
are folded to lower case, as are input tokens. When it is
<code class="literal">true</code>, words and tokens are not folded to lower case,
but are compared as-is.
</p><p>
An asterisk (<code class="literal">*</code>) can be placed at the end of a synonym
in the configuration file. This indicates that the synonym is a prefix.
The asterisk is ignored when the entry is used in
<code class="function">to_tsvector()</code>, but when it is used in
<code class="function">to_tsquery()</code>, the result will be a query item with
the prefix match marker (see
<a class="xref" href="textsearch-controls.html#TEXTSEARCH-PARSING-QUERIES" title="12.3.2. Parsing Queries">Section 12.3.2</a>).
For example, suppose we have these entries in
<code class="filename">$SHAREDIR/tsearch_data/synonym_sample.syn</code>:
</p><pre class="programlisting">
postgres pgsql
postgresql pgsql
postgre pgsql
gogle googl
indices index*
</pre><p>
Then we will get these results:
</p><pre class="screen">
mydb=# CREATE TEXT SEARCH DICTIONARY syn (template=synonym, synonyms='synonym_sample');
mydb=# SELECT ts_lexize('syn', 'indices');
ts_lexize
-----------
{index}
(1 row)
mydb=# CREATE TEXT SEARCH CONFIGURATION tst (copy=simple);
mydb=# ALTER TEXT SEARCH CONFIGURATION tst ALTER MAPPING FOR asciiword WITH syn;
mydb=# SELECT to_tsvector('tst', 'indices');
to_tsvector
-------------
'index':1
(1 row)
mydb=# SELECT to_tsquery('tst', 'indices');
to_tsquery
------------
'index':*
(1 row)
mydb=# SELECT 'indexes are very useful'::tsvector;
tsvector
---------------------------------
'are' 'indexes' 'useful' 'very'
(1 row)
mydb=# SELECT 'indexes are very useful'::tsvector @@ to_tsquery('tst', 'indices');
?column?
----------
t
(1 row)
</pre><p>
</p></div><div class="sect2" id="TEXTSEARCH-THESAURUS"><div class="titlepage"><div><div><h3 class="title">12.6.4. Thesaurus Dictionary</h3></div></div></div><p>
A thesaurus dictionary (sometimes abbreviated as <acronym class="acronym">TZ</acronym>) is
a collection of words that includes information about the relationships
of words and phrases, i.e., broader terms (<acronym class="acronym">BT</acronym>), narrower
terms (<acronym class="acronym">NT</acronym>), preferred terms, non-preferred terms, related
terms, etc.
</p><p>
Basically a thesaurus dictionary replaces all non-preferred terms by one
preferred term and, optionally, preserves the original terms for indexing
as well. <span class="productname">PostgreSQL</span>'s current implementation of the
thesaurus dictionary is an extension of the synonym dictionary with added
<em class="firstterm">phrase</em> support. A thesaurus dictionary requires
a configuration file of the following format:
</p><pre class="programlisting">
# this is a comment
sample word(s) : indexed word(s)
more sample word(s) : more indexed word(s)
...
</pre><p>
where the colon (<code class="symbol">:</code>) symbol acts as a delimiter between a
phrase and its replacement.
</p><p>
A thesaurus dictionary uses a <em class="firstterm">subdictionary</em> (which
is specified in the dictionary's configuration) to normalize the input
text before checking for phrase matches. It is only possible to select one
subdictionary. An error is reported if the subdictionary fails to
recognize a word. In that case, you should remove the use of the word or
teach the subdictionary about it. You can place an asterisk
(<code class="symbol">*</code>) at the beginning of an indexed word to skip applying
the subdictionary to it, but all sample words <span class="emphasis"><em>must</em></span> be known
to the subdictionary.
</p><p>
The thesaurus dictionary chooses the longest match if there are multiple
phrases matching the input, and ties are broken by using the last
definition.
</p><p>
Specific stop words recognized by the subdictionary cannot be
specified; instead use <code class="literal">?</code> to mark the location where any
stop word can appear. For example, assuming that <code class="literal">a</code> and
<code class="literal">the</code> are stop words according to the subdictionary:
</p><pre class="programlisting">
? one ? two : swsw
</pre><p>
matches <code class="literal">a one the two</code> and <code class="literal">the one a two</code>;
both would be replaced by <code class="literal">swsw</code>.
</p><p>
Since a thesaurus dictionary has the capability to recognize phrases it
must remember its state and interact with the parser. A thesaurus dictionary
uses these assignments to check if it should handle the next word or stop
accumulation. The thesaurus dictionary must be configured
carefully. For example, if the thesaurus dictionary is assigned to handle
only the <code class="literal">asciiword</code> token, then a thesaurus dictionary
definition like <code class="literal">one 7</code> will not work since token type
<code class="literal">uint</code> is not assigned to the thesaurus dictionary.
</p><div class="caution"><h3 class="title">Caution</h3><p>
Thesauruses are used during indexing so any change in the thesaurus
dictionary's parameters <span class="emphasis"><em>requires</em></span> reindexing.
For most other dictionary types, small changes such as adding or
removing stopwords does not force reindexing.
</p></div><div class="sect3" id="TEXTSEARCH-THESAURUS-CONFIG"><div class="titlepage"><div><div><h4 class="title">12.6.4.1. Thesaurus Configuration</h4></div></div></div><p>
To define a new thesaurus dictionary, use the <code class="literal">thesaurus</code>
template. For example:
</p><pre class="programlisting">
CREATE TEXT SEARCH DICTIONARY thesaurus_simple (
TEMPLATE = thesaurus,
DictFile = mythesaurus,
Dictionary = pg_catalog.english_stem
);
</pre><p>
Here:
</p><div class="itemizedlist"><ul class="itemizedlist compact" style="list-style-type: bullet; "><li class="listitem" style="list-style-type: disc"><p>
<code class="literal">thesaurus_simple</code> is the new dictionary's name
</p></li><li class="listitem" style="list-style-type: disc"><p>
<code class="literal">mythesaurus</code> is the base name of the thesaurus
configuration file.
(Its full name will be <code class="filename">$SHAREDIR/tsearch_data/mythesaurus.ths</code>,
where <code class="literal">$SHAREDIR</code> means the installation shared-data
directory.)
</p></li><li class="listitem" style="list-style-type: disc"><p>
<code class="literal">pg_catalog.english_stem</code> is the subdictionary (here,
a Snowball English stemmer) to use for thesaurus normalization.
Notice that the subdictionary will have its own
configuration (for example, stop words), which is not shown here.
</p></li></ul></div><p>
Now it is possible to bind the thesaurus dictionary <code class="literal">thesaurus_simple</code>
to the desired token types in a configuration, for example:
</p><pre class="programlisting">
ALTER TEXT SEARCH CONFIGURATION russian
ALTER MAPPING FOR asciiword, asciihword, hword_asciipart
WITH thesaurus_simple;
</pre><p>
</p></div><div class="sect3" id="TEXTSEARCH-THESAURUS-EXAMPLES"><div class="titlepage"><div><div><h4 class="title">12.6.4.2. Thesaurus Example</h4></div></div></div><p>
Consider a simple astronomical thesaurus <code class="literal">thesaurus_astro</code>,
which contains some astronomical word combinations:
</p><pre class="programlisting">
supernovae stars : sn
crab nebulae : crab
</pre><p>
Below we create a dictionary and bind some token types to
an astronomical thesaurus and English stemmer:
</p><pre class="programlisting">
CREATE TEXT SEARCH DICTIONARY thesaurus_astro (
TEMPLATE = thesaurus,
DictFile = thesaurus_astro,
Dictionary = english_stem
);
ALTER TEXT SEARCH CONFIGURATION russian
ALTER MAPPING FOR asciiword, asciihword, hword_asciipart
WITH thesaurus_astro, english_stem;
</pre><p>
Now we can see how it works.
<code class="function">ts_lexize</code> is not very useful for testing a thesaurus,
because it treats its input as a single token. Instead we can use
<code class="function">plainto_tsquery</code> and <code class="function">to_tsvector</code>
which will break their input strings into multiple tokens:
</p><pre class="screen">
SELECT plainto_tsquery('supernova star');
plainto_tsquery
-----------------
'sn'
SELECT to_tsvector('supernova star');
to_tsvector
-------------
'sn':1
</pre><p>
In principle, one can use <code class="function">to_tsquery</code> if you quote
the argument:
</p><pre class="screen">
SELECT to_tsquery('''supernova star''');
to_tsquery
------------
'sn'
</pre><p>
Notice that <code class="literal">supernova star</code> matches <code class="literal">supernovae
stars</code> in <code class="literal">thesaurus_astro</code> because we specified
the <code class="literal">english_stem</code> stemmer in the thesaurus definition.
The stemmer removed the <code class="literal">e</code> and <code class="literal">s</code>.
</p><p>
To index the original phrase as well as the substitute, just include it
in the right-hand part of the definition:
</p><pre class="screen">
supernovae stars : sn supernovae stars
SELECT plainto_tsquery('supernova star');
plainto_tsquery
-----------------------------
'sn' & 'supernova' & 'star'
</pre><p>
</p></div></div><div class="sect2" id="TEXTSEARCH-ISPELL-DICTIONARY"><div class="titlepage"><div><div><h3 class="title">12.6.5. <span class="application">Ispell</span> Dictionary</h3></div></div></div><p>
The <span class="application">Ispell</span> dictionary template supports
<em class="firstterm">morphological dictionaries</em>, which can normalize many
different linguistic forms of a word into the same lexeme. For example,
an English <span class="application">Ispell</span> dictionary can match all declensions and
conjugations of the search term <code class="literal">bank</code>, e.g.,
<code class="literal">banking</code>, <code class="literal">banked</code>, <code class="literal">banks</code>,
<code class="literal">banks'</code>, and <code class="literal">bank's</code>.
</p><p>
The standard <span class="productname">PostgreSQL</span> distribution does
not include any <span class="application">Ispell</span> configuration files.
Dictionaries for a large number of languages are available from <a class="ulink" href="https://www.cs.hmc.edu/~geoff/ispell.html" target="_top">Ispell</a>.
Also, some more modern dictionary file formats are supported — <a class="ulink" href="https://en.wikipedia.org/wiki/MySpell" target="_top">MySpell</a> (OO < 2.0.1)
and <a class="ulink" href="https://sourceforge.net/projects/hunspell/" target="_top">Hunspell</a>
(OO >= 2.0.2). A large list of dictionaries is available on the <a class="ulink" href="https://wiki.openoffice.org/wiki/Dictionaries" target="_top">OpenOffice
Wiki</a>.
</p><p>
To create an <span class="application">Ispell</span> dictionary perform these steps:
</p><div class="itemizedlist"><ul class="itemizedlist compact" style="list-style-type: bullet; "><li class="listitem" style="list-style-type: disc"><p>
download dictionary configuration files. <span class="productname">OpenOffice</span>
extension files have the <code class="filename">.oxt</code> extension. It is necessary
to extract <code class="filename">.aff</code> and <code class="filename">.dic</code> files, change
extensions to <code class="filename">.affix</code> and <code class="filename">.dict</code>. For some
dictionary files it is also needed to convert characters to the UTF-8
encoding with commands (for example, for a Norwegian language dictionary):
</p><pre class="programlisting">
iconv -f ISO_8859-1 -t UTF-8 -o nn_no.affix nn_NO.aff
iconv -f ISO_8859-1 -t UTF-8 -o nn_no.dict nn_NO.dic
</pre><p>
</p></li><li class="listitem" style="list-style-type: disc"><p>
copy files to the <code class="filename">$SHAREDIR/tsearch_data</code> directory
</p></li><li class="listitem" style="list-style-type: disc"><p>
load files into PostgreSQL with the following command:
</p><pre class="programlisting">
CREATE TEXT SEARCH DICTIONARY english_hunspell (
TEMPLATE = ispell,
DictFile = en_us,
AffFile = en_us,
Stopwords = english);
</pre><p>
</p></li></ul></div><p>
Here, <code class="literal">DictFile</code>, <code class="literal">AffFile</code>, and <code class="literal">StopWords</code>
specify the base names of the dictionary, affixes, and stop-words files.
The stop-words file has the same format explained above for the
<code class="literal">simple</code> dictionary type. The format of the other files is
not specified here but is available from the above-mentioned web sites.
</p><p>
Ispell dictionaries usually recognize a limited set of words, so they
should be followed by another broader dictionary; for
example, a Snowball dictionary, which recognizes everything.
</p><p>
The <code class="filename">.affix</code> file of <span class="application">Ispell</span> has the following
structure:
</p><pre class="programlisting">
prefixes
flag *A:
. > RE # As in enter > reenter
suffixes
flag T:
E > ST # As in late > latest
[^AEIOU]Y > -Y,IEST # As in dirty > dirtiest
[AEIOU]Y > EST # As in gray > grayest
[^EY] > EST # As in small > smallest
</pre><p>
</p><p>
And the <code class="filename">.dict</code> file has the following structure:
</p><pre class="programlisting">
lapse/ADGRS
lard/DGRS
large/PRTY
lark/MRS
</pre><p>
</p><p>
Format of the <code class="filename">.dict</code> file is:
</p><pre class="programlisting">
basic_form/affix_class_name
</pre><p>
</p><p>
In the <code class="filename">.affix</code> file every affix flag is described in the
following format:
</p><pre class="programlisting">
condition > [-stripping_letters,] adding_affix
</pre><p>
</p><p>
Here, condition has a format similar to the format of regular expressions.
It can use groupings <code class="literal">[...]</code> and <code class="literal">[^...]</code>.
For example, <code class="literal">[AEIOU]Y</code> means that the last letter of the word
is <code class="literal">"y"</code> and the penultimate letter is <code class="literal">"a"</code>,
<code class="literal">"e"</code>, <code class="literal">"i"</code>, <code class="literal">"o"</code> or <code class="literal">"u"</code>.
<code class="literal">[^EY]</code> means that the last letter is neither <code class="literal">"e"</code>
nor <code class="literal">"y"</code>.
</p><p>
Ispell dictionaries support splitting compound words;
a useful feature.
Notice that the affix file should specify a special flag using the
<code class="literal">compoundwords controlled</code> statement that marks dictionary
words that can participate in compound formation:
</p><pre class="programlisting">
compoundwords controlled z
</pre><p>
Here are some examples for the Norwegian language:
</p><pre class="programlisting">
SELECT ts_lexize('norwegian_ispell', 'overbuljongterningpakkmesterassistent');
{over,buljong,terning,pakk,mester,assistent}
SELECT ts_lexize('norwegian_ispell', 'sjokoladefabrikk');
{sjokoladefabrikk,sjokolade,fabrikk}
</pre><p>
</p><p>
<span class="application">MySpell</span> format is a subset of <span class="application">Hunspell</span>.
The <code class="filename">.affix</code> file of <span class="application">Hunspell</span> has the following
structure:
</p><pre class="programlisting">
PFX A Y 1
PFX A 0 re .
SFX T N 4
SFX T 0 st e
SFX T y iest [^aeiou]y
SFX T 0 est [aeiou]y
SFX T 0 est [^ey]
</pre><p>
</p><p>
The first line of an affix class is the header. Fields of an affix rules are
listed after the header:
</p><div class="itemizedlist"><ul class="itemizedlist compact" style="list-style-type: bullet; "><li class="listitem" style="list-style-type: disc"><p>
parameter name (PFX or SFX)
</p></li><li class="listitem" style="list-style-type: disc"><p>
flag (name of the affix class)
</p></li><li class="listitem" style="list-style-type: disc"><p>
stripping characters from beginning (at prefix) or end (at suffix) of the
word
</p></li><li class="listitem" style="list-style-type: disc"><p>
adding affix
</p></li><li class="listitem" style="list-style-type: disc"><p>
condition that has a format similar to the format of regular expressions.
</p></li></ul></div><p>
The <code class="filename">.dict</code> file looks like the <code class="filename">.dict</code> file of
<span class="application">Ispell</span>:
</p><pre class="programlisting">
larder/M
lardy/RT
large/RSPMYT
largehearted
</pre><p>
</p><div class="note"><h3 class="title">Note</h3><p>
<span class="application">MySpell</span> does not support compound words.
<span class="application">Hunspell</span> has sophisticated support for compound words. At
present, <span class="productname">PostgreSQL</span> implements only the basic
compound word operations of Hunspell.
</p></div></div><div class="sect2" id="TEXTSEARCH-SNOWBALL-DICTIONARY"><div class="titlepage"><div><div><h3 class="title">12.6.6. <span class="application">Snowball</span> Dictionary</h3></div></div></div><p>
The <span class="application">Snowball</span> dictionary template is based on a project
by Martin Porter, inventor of the popular Porter's stemming algorithm
for the English language. Snowball now provides stemming algorithms for
many languages (see the <a class="ulink" href="https://snowballstem.org/" target="_top">Snowball
site</a> for more information). Each algorithm understands how to
reduce common variant forms of words to a base, or stem, spelling within
its language. A Snowball dictionary requires a <code class="literal">language</code>
parameter to identify which stemmer to use, and optionally can specify a
<code class="literal">stopword</code> file name that gives a list of words to eliminate.
(<span class="productname">PostgreSQL</span>'s standard stopword lists are also
provided by the Snowball project.)
For example, there is a built-in definition equivalent to
</p><pre class="programlisting">
CREATE TEXT SEARCH DICTIONARY english_stem (
TEMPLATE = snowball,
Language = english,
StopWords = english
);
</pre><p>
The stopword file format is the same as already explained.
</p><p>
A <span class="application">Snowball</span> dictionary recognizes everything, whether
or not it is able to simplify the word, so it should be placed
at the end of the dictionary list. It is useless to have it
before any other dictionary because a token will never pass through it to
the next dictionary.
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