{"Entry":{"collection":"fts","key":"dictionary-esperanto_stem","name":"esperanto_stem","aliases":[],"metadata":{"aliases":[],"category":"Dictionaries","content_hash":"21e0d60f44e6ad9108938328ccf05b5dd49db1d4bf009288ecda87e31afd6570","imported_at":"2026-09-30T00:40:47.571189+08:00","name":"esperanto_stem","name_zh":"","slug":"dictionary-esperanto_stem","summary":"Snowball stemmer for esperanto language."}},"Definition":{"Collection":"fts","Key":"dictionary-esperanto_stem","SourceDatabase":"center","Version":"20","SourceTable":"text_search_component","SourceKey":"dictionary-esperanto_stem","SourceRevision":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","Facts":{"aliases":[],"attributes":{"ascii_language":"esperanto","dictionary":"esperanto_stem","language":"esperanto","stopword_lines":0,"stopword_sha256":"","stopwords":"","template":"snowball"},"comparison_data":{"ascii_language":"esperanto","dictionary":"esperanto_stem","language":"esperanto","stopword_lines":0,"stopword_sha256":"","stopwords":"","template":"snowball"},"comparison_hash":"f2f16a16922cd461c582130d38c4825292453b51052e4f2f5e09c5e6ab55cfef","description":["Snowball stemmer for esperanto language."],"facts":[{"label":"Language","value":"esperanto"},{"label":"Ascii language","value":"esperanto"},{"label":"Stopword lines","value":"0"},{"label":"Dictionary","value":"esperanto_stem"},{"label":"Template","value":"snowball"}],"manual_html":"\u003cdiv class=\"sect2\" id=\"TEXTSEARCH-SNOWBALL-DICTIONARY\"\u003e\n\u003cdiv class=\"titlepage\"\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"title\"\u003e12.6.6. \u003cspan class=\"application\"\u003eSnowball\u003c/span\u003e Dictionary \u003c/h3\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eThe \u003cspan class=\"application\"\u003eSnowball\u003c/span\u003e 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 \u003ca class=\"ulink\" href=\"https://snowballstem.org/\"\u003eSnowball site\u003c/a\u003e 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 \u003ccode class=\"literal\"\u003elanguage\u003c/code\u003e parameter to identify which stemmer to use, and optionally can specify a \u003ccode class=\"literal\"\u003estopword\u003c/code\u003e file name that gives a list of words to eliminate. (\u003cspan class=\"productname\"\u003ePostgreSQL\u003c/span\u003e's standard stopword lists are also provided by the Snowball project.)\u003c/p\u003e\n\u003cp\u003eThe available values of the \u003ccode class=\"literal\"\u003elanguage\u003c/code\u003e parameter are: \u003ccode class=\"literal\"\u003earabic\u003c/code\u003e, \u003ccode class=\"literal\"\u003earmenian\u003c/code\u003e, \u003ccode class=\"literal\"\u003ebasque\u003c/code\u003e, \u003ccode class=\"literal\"\u003ecatalan\u003c/code\u003e, \u003ccode class=\"literal\"\u003edanish\u003c/code\u003e, \u003ccode class=\"literal\"\u003edutch\u003c/code\u003e, \u003ccode class=\"literal\"\u003edutch_porter\u003c/code\u003e, \u003ccode class=\"literal\"\u003eenglish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eesperanto\u003c/code\u003e, \u003ccode class=\"literal\"\u003eestonian\u003c/code\u003e, \u003ccode class=\"literal\"\u003efinnish\u003c/code\u003e, \u003ccode class=\"literal\"\u003efrench\u003c/code\u003e, \u003ccode class=\"literal\"\u003egerman\u003c/code\u003e, \u003ccode class=\"literal\"\u003egreek\u003c/code\u003e, \u003ccode class=\"literal\"\u003ehindi\u003c/code\u003e, \u003ccode class=\"literal\"\u003ehungarian\u003c/code\u003e, \u003ccode class=\"literal\"\u003eindonesian\u003c/code\u003e, \u003ccode class=\"literal\"\u003eirish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eitalian\u003c/code\u003e, \u003ccode class=\"literal\"\u003elithuanian\u003c/code\u003e, \u003ccode class=\"literal\"\u003enepali\u003c/code\u003e, \u003ccode class=\"literal\"\u003enorwegian\u003c/code\u003e, \u003ccode class=\"literal\"\u003epolish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eporter\u003c/code\u003e, \u003ccode class=\"literal\"\u003eportuguese\u003c/code\u003e, \u003ccode class=\"literal\"\u003eromanian\u003c/code\u003e, \u003ccode class=\"literal\"\u003erussian\u003c/code\u003e, \u003ccode class=\"literal\"\u003eserbian\u003c/code\u003e, \u003ccode class=\"literal\"\u003espanish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eswedish\u003c/code\u003e, \u003ccode class=\"literal\"\u003etamil\u003c/code\u003e, \u003ccode class=\"literal\"\u003eturkish\u003c/code\u003e, and \u003ccode class=\"literal\"\u003eyiddish\u003c/code\u003e. The \u003ccode class=\"literal\"\u003eporter\u003c/code\u003e algorithm is an old stemmer for English, and the \u003ccode class=\"literal\"\u003edutch_porter\u003c/code\u003e algorithm is an old stemmer for Dutch (it was called \u003ccode class=\"literal\"\u003edutch\u003c/code\u003e in \u003cspan class=\"productname\"\u003ePostgreSQL\u003c/span\u003e releases before 19). The rest are the currently-recommended stemmers for their respective languages. All these algorithms except \u003ccode class=\"literal\"\u003eporter\u003c/code\u003e and \u003ccode class=\"literal\"\u003edutch_porter\u003c/code\u003e have built-in dictionaries provided, most with stopword lists attached. For example, there is a built-in definition equivalent to\u003c/p\u003e\n\u003cpre class=\"programlisting\"\u003eCREATE TEXT SEARCH DICTIONARY english_stem (\n    TEMPLATE = snowball,\n    Language = english,\n    StopWords = english\n);\n\u003c/pre\u003e\n\u003cp\u003eThe stopword file format is the same as already explained.\u003c/p\u003e\n\u003cp\u003eA \u003cspan class=\"application\"\u003eSnowball\u003c/span\u003e 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.\u003c/p\u003e\n\u003c/div\u003e","manual_path":"/docs/devel/textsearch-dictionaries.html#TEXTSEARCH-SNOWBALL-DICTIONARY","related":[{"label":"snowball template","url":"/wiki/fts/template-snowball/?v=20"},{"label":"esperanto configuration","url":"/wiki/fts/configuration-esperanto/?v=20"}],"release":{"catalog_fingerprint":"398fbb9f262264053c02fbf79f88be0a6770c1473faa6ecd5931d6ec41b8258b","channel":"devel","label":"20devel","major":"20","ref":"https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2","revision":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","source_sha256":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","source_snapshot_utc":"26-Sep-2026 20:22"},"sections":[],"signature":"","sources":[{"label":"Matching PostgreSQL source archive","sha256":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","url":"https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2"},{"label":"PostgreSQL 20 English manual","path":"textsearch-dictionaries.html","sha256":"38c6f6073ed98b8e321cad040c89265f00a6fe755aa68f0f1a28a1ad1457c9c0","url":"/docs/devel/textsearch-dictionaries.html#TEXTSEARCH-SNOWBALL-DICTIONARY"}],"tables":[]},"ManualEvidence":{"manual_path":"/docs/devel/textsearch-dictionaries.html#TEXTSEARCH-SNOWBALL-DICTIONARY","release":{"catalog_fingerprint":"398fbb9f262264053c02fbf79f88be0a6770c1473faa6ecd5931d6ec41b8258b","channel":"devel","label":"20devel","major":"20","ref":"https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2","revision":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","source_sha256":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","source_snapshot_utc":"26-Sep-2026 20:22"},"sources":[{"label":"Matching PostgreSQL source archive","sha256":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","url":"https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2"},{"label":"PostgreSQL 20 English manual","path":"textsearch-dictionaries.html","sha256":"38c6f6073ed98b8e321cad040c89265f00a6fe755aa68f0f1a28a1ad1457c9c0","url":"/docs/devel/textsearch-dictionaries.html#TEXTSEARCH-SNOWBALL-DICTIONARY"}]},"MeasuredEvidence":{}},"Text":{"Collection":"fts","Key":"dictionary-esperanto_stem","SourceDatabase":"center","Version":"20","Locale":"en","Title":"esperanto_stem","Summary":"Snowball stemmer for esperanto language.","BodyHTML":"\u003cdiv id=\"TEXTSEARCH-SNOWBALL-DICTIONARY\"\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\n\u003ch3\u003e12.6.6. \u003cspan\u003eSnowball\u003c/span\u003e Dictionary \u003c/h3\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eThe \u003cspan\u003eSnowball\u003c/span\u003e dictionary template is based on a project by Martin Porter, inventor of the popular Porter\u0026#39;s stemming algorithm for the English language. Snowball now provides stemming algorithms for many languages (see the \u003ca href=\"https://snowballstem.org/\" rel=\"nofollow\"\u003eSnowball site\u003c/a\u003e 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 \u003ccode\u003elanguage\u003c/code\u003e parameter to identify which stemmer to use, and optionally can specify a \u003ccode\u003estopword\u003c/code\u003e file name that gives a list of words to eliminate. (\u003cspan\u003ePostgreSQL\u003c/span\u003e\u0026#39;s standard stopword lists are also provided by the Snowball project.)\u003c/p\u003e\n\u003cp\u003eThe available values of the \u003ccode\u003elanguage\u003c/code\u003e parameter are: \u003ccode\u003earabic\u003c/code\u003e, \u003ccode\u003earmenian\u003c/code\u003e, \u003ccode\u003ebasque\u003c/code\u003e, \u003ccode\u003ecatalan\u003c/code\u003e, \u003ccode\u003edanish\u003c/code\u003e, \u003ccode\u003edutch\u003c/code\u003e, \u003ccode\u003edutch_porter\u003c/code\u003e, \u003ccode\u003eenglish\u003c/code\u003e, \u003ccode\u003eesperanto\u003c/code\u003e, \u003ccode\u003eestonian\u003c/code\u003e, \u003ccode\u003efinnish\u003c/code\u003e, \u003ccode\u003efrench\u003c/code\u003e, \u003ccode\u003egerman\u003c/code\u003e, \u003ccode\u003egreek\u003c/code\u003e, \u003ccode\u003ehindi\u003c/code\u003e, \u003ccode\u003ehungarian\u003c/code\u003e, \u003ccode\u003eindonesian\u003c/code\u003e, \u003ccode\u003eirish\u003c/code\u003e, \u003ccode\u003eitalian\u003c/code\u003e, \u003ccode\u003elithuanian\u003c/code\u003e, \u003ccode\u003enepali\u003c/code\u003e, \u003ccode\u003enorwegian\u003c/code\u003e, \u003ccode\u003epolish\u003c/code\u003e, \u003ccode\u003eporter\u003c/code\u003e, \u003ccode\u003eportuguese\u003c/code\u003e, \u003ccode\u003eromanian\u003c/code\u003e, \u003ccode\u003erussian\u003c/code\u003e, \u003ccode\u003eserbian\u003c/code\u003e, \u003ccode\u003espanish\u003c/code\u003e, \u003ccode\u003eswedish\u003c/code\u003e, \u003ccode\u003etamil\u003c/code\u003e, \u003ccode\u003eturkish\u003c/code\u003e, and \u003ccode\u003eyiddish\u003c/code\u003e. The \u003ccode\u003eporter\u003c/code\u003e algorithm is an old stemmer for English, and the \u003ccode\u003edutch_porter\u003c/code\u003e algorithm is an old stemmer for Dutch (it was called \u003ccode\u003edutch\u003c/code\u003e in \u003cspan\u003ePostgreSQL\u003c/span\u003e releases before 19). The rest are the currently-recommended stemmers for their respective languages. All these algorithms except \u003ccode\u003eporter\u003c/code\u003e and \u003ccode\u003edutch_porter\u003c/code\u003e have built-in dictionaries provided, most with stopword lists attached. For example, there is a built-in definition equivalent to\u003c/p\u003e\n\u003cpre\u003eCREATE TEXT SEARCH DICTIONARY english_stem (\n    TEMPLATE = snowball,\n    Language = english,\n    StopWords = english\n);\n\u003c/pre\u003e\n\u003cp\u003eThe stopword file format is the same as already explained.\u003c/p\u003e\n\u003cp\u003eA \u003cspan\u003eSnowball\u003c/span\u003e 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.\u003c/p\u003e\n\u003c/div\u003e","SourceRevision":"4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41","ContentHash":"6067327c9193da5eaba3822dceace38f07907b5b7285c4b906d49aabad9cdec0","Payload":{"description":["Snowball stemmer for esperanto language."],"manual_html":"\u003cdiv class=\"sect2\" id=\"TEXTSEARCH-SNOWBALL-DICTIONARY\"\u003e\n\u003cdiv class=\"titlepage\"\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\n\u003ch3 class=\"title\"\u003e12.6.6. \u003cspan class=\"application\"\u003eSnowball\u003c/span\u003e Dictionary \u003c/h3\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eThe \u003cspan class=\"application\"\u003eSnowball\u003c/span\u003e 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 \u003ca class=\"ulink\" href=\"https://snowballstem.org/\"\u003eSnowball site\u003c/a\u003e 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 \u003ccode class=\"literal\"\u003elanguage\u003c/code\u003e parameter to identify which stemmer to use, and optionally can specify a \u003ccode class=\"literal\"\u003estopword\u003c/code\u003e file name that gives a list of words to eliminate. (\u003cspan class=\"productname\"\u003ePostgreSQL\u003c/span\u003e's standard stopword lists are also provided by the Snowball project.)\u003c/p\u003e\n\u003cp\u003eThe available values of the \u003ccode class=\"literal\"\u003elanguage\u003c/code\u003e parameter are: \u003ccode class=\"literal\"\u003earabic\u003c/code\u003e, \u003ccode class=\"literal\"\u003earmenian\u003c/code\u003e, \u003ccode class=\"literal\"\u003ebasque\u003c/code\u003e, \u003ccode class=\"literal\"\u003ecatalan\u003c/code\u003e, \u003ccode class=\"literal\"\u003edanish\u003c/code\u003e, \u003ccode class=\"literal\"\u003edutch\u003c/code\u003e, \u003ccode class=\"literal\"\u003edutch_porter\u003c/code\u003e, \u003ccode class=\"literal\"\u003eenglish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eesperanto\u003c/code\u003e, \u003ccode class=\"literal\"\u003eestonian\u003c/code\u003e, \u003ccode class=\"literal\"\u003efinnish\u003c/code\u003e, \u003ccode class=\"literal\"\u003efrench\u003c/code\u003e, \u003ccode class=\"literal\"\u003egerman\u003c/code\u003e, \u003ccode class=\"literal\"\u003egreek\u003c/code\u003e, \u003ccode class=\"literal\"\u003ehindi\u003c/code\u003e, \u003ccode class=\"literal\"\u003ehungarian\u003c/code\u003e, \u003ccode class=\"literal\"\u003eindonesian\u003c/code\u003e, \u003ccode class=\"literal\"\u003eirish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eitalian\u003c/code\u003e, \u003ccode class=\"literal\"\u003elithuanian\u003c/code\u003e, \u003ccode class=\"literal\"\u003enepali\u003c/code\u003e, \u003ccode class=\"literal\"\u003enorwegian\u003c/code\u003e, \u003ccode class=\"literal\"\u003epolish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eporter\u003c/code\u003e, \u003ccode class=\"literal\"\u003eportuguese\u003c/code\u003e, \u003ccode class=\"literal\"\u003eromanian\u003c/code\u003e, \u003ccode class=\"literal\"\u003erussian\u003c/code\u003e, \u003ccode class=\"literal\"\u003eserbian\u003c/code\u003e, \u003ccode class=\"literal\"\u003espanish\u003c/code\u003e, \u003ccode class=\"literal\"\u003eswedish\u003c/code\u003e, \u003ccode class=\"literal\"\u003etamil\u003c/code\u003e, \u003ccode class=\"literal\"\u003eturkish\u003c/code\u003e, and \u003ccode class=\"literal\"\u003eyiddish\u003c/code\u003e. The \u003ccode class=\"literal\"\u003eporter\u003c/code\u003e algorithm is an old stemmer for English, and the \u003ccode class=\"literal\"\u003edutch_porter\u003c/code\u003e algorithm is an old stemmer for Dutch (it was called \u003ccode class=\"literal\"\u003edutch\u003c/code\u003e in \u003cspan class=\"productname\"\u003ePostgreSQL\u003c/span\u003e releases before 19). The rest are the currently-recommended stemmers for their respective languages. All these algorithms except \u003ccode class=\"literal\"\u003eporter\u003c/code\u003e and \u003ccode class=\"literal\"\u003edutch_porter\u003c/code\u003e have built-in dictionaries provided, most with stopword lists attached. For example, there is a built-in definition equivalent to\u003c/p\u003e\n\u003cpre class=\"programlisting\"\u003eCREATE TEXT SEARCH DICTIONARY english_stem (\n    TEMPLATE = snowball,\n    Language = english,\n    StopWords = english\n);\n\u003c/pre\u003e\n\u003cp\u003eThe stopword file format is the same as already explained.\u003c/p\u003e\n\u003cp\u003eA \u003cspan class=\"application\"\u003eSnowball\u003c/span\u003e 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.\u003c/p\u003e\n\u003c/div\u003e","related":[{"label":"snowball template","url":"/wiki/fts/template-snowball/?v=20"},{"label":"esperanto configuration","url":"/wiki/fts/configuration-esperanto/?v=20"}],"sections":[],"tables":[]}},"RequestedLocale":"zh-Hans","Fallback":true,"Versions":["19","20"],"Locales":["en"],"Signatures":null,"Spellings":null,"SQLState":null,"Evidence":null}