Online Access

Access entry points

You may acces the data online using:

Querying data using SPARQL

SPARQL is a standard language for querying linked data. We give some sample queries that may be used to query existing data. Note that this public service is limited and queries that are too long to process will be canceled automatically.

Getting all German translations of the English lexical entry cat__noun__1

 ?t dbnary:isTranslationOf dbnary-eng:cat__Noun__1 ; 
 dbnary:targetLanguage lexvo:deu ;
 dbnary:writtenForm ?f .
 OPTIONAL {?t dbnary:gloss ?o}

Counting all available translations to French

PREFIX lexvo: <>
PREFIX dbnary: <>

SELECT count(?t) WHERE { ?t dbnary:targetLanguage lexvo:fra . }

Counting translations to Bambara by source language

SELECT count(?t) , ?l WHERE { 
 ?t dbnary:targetLanguage lexvo:bam ; 
 dbnary:isTranslationOf ?e . 
 ?e lime:language ?l}

Getting a flat list of all “nym” relations

This query will likely time out on the kaiko server if you do not use the limit argument. It may be easily used on a mirror server that you can set up using the current dumps.

SELECT distinct ?f ?rel ?t 
 ?f dbnary:describes ?lf. 
 { ?lf ?rel ?t. 
 ?t a dbnary:Page} UNION 
 {?lf ontolex:sense ?sf. 
 ?sf ?rel ?t. 
 ?t a dbnary:Page. } 
 ?lf lime:language "fr". } LIMIT 100

Get statistics on number of relations per graphs

This query will give you a stat that is the same as the  stats….csv file.

Select ?g ?p count(?p) as ?count where { 
  Graph ?g { ?s ?p ?o } 
} group by ?p ?g 
  order by desc (?g) desc(?count)

Counting the number of russian/turkish translation pairs that are connected through an English Lemma or sense

 ?trans1 dbnary:isTranslationOf ?e ; 
 dbnary:targetLanguage lexvo:rus ;
 dbnary:writtenForm ?r .
 ?trans2 dbnary:isTranslationOf ?e ; 
 dbnary:targetLanguage lexvo:tur ;
 dbnary:writtenForm ?t .

Getting all translations to Wolof

PREFIX lexvo: <>
PREFIX dbnary: <>
PREFIX lemon: <>
SELECT ?source, ?l, ?target WHERE { 
 ?t dbnary:targetLanguage lexvo:wol ; 
 dbnary:isTranslationOf ?e ;
 dbnary:writtenForm ?target. 
 ?e lime:language ?l ;
 ontolex:canonicalForm ?f.
 ?f ontolex:writtenRep ?source

Pre-computing entity to label relations using a SPARQL 1.1 inference

This is to be done by the admin before computing facetted browser indexes so that Entity label lookup work in facetted browser.

PREFIX lemon: <>
SELECT ?l ?o
 ?o lemon:canonicalForm/lemon:writtenRep ?l .

Getting all verbal locution, along with several info

PREFIX dbnary: <>
PREFIX eng: <>
PREFIX lexvo: <>

select  distinct ?w, ?syn, ?ant, ?sn, ?ds, ?sew where {
	?l a ontolex:MultiWordExpression; lime:language "fr"; ontolex:canonicalForm ?f ; lexinfo:partOfSpeech lexinfo:verb ; ontolex:sense ?s .
        ?f ontolex:writtenRep ?w .
        ?s skos:definition ?d ; dbnary:senseNumber ?sn .
        ?d rdf:value ?ds .
        OPTIONAL { ?s skos:example ?se . ?se rdf:value ?sew .}
        OPTIONAL { ?l dbnary:synonym ?syn ; dbnary:antonym ?ant .}

Counting the number of English senses with a translation in French

 ?t dbnary:isTranslationOf ?es ; 
 dbnary:targetLanguage lexvo:fra ;
 dbnary:writtenForm ?f .
 ?es a ontolex:LexicalSense .