GraphDB supports FTS Lucene plugin to build RDF 'molecule' to index texts efficiently. However, when there is a typo (missspell) in the word your are searching, Lucene would not retrieve a result. I wonder if it is possible to implement a FuzzyQuery based on the Damerau-Levenshtein algorithm on top the Lucene Index in GraphDB for FTS. That way even if the word is not correctly spell you can get a list of more 'closed' words based on an edit distance similarity.
This is the index I have created for indexing labels of NounSynset in WordNet RDF.
PREFIX wn20schema: <http://www.w3.org/2006/03/wn/wn20/schema/>
INSERT DATA {
luc:index luc:setParam "uris" .
luc:include luc:setParam "literals" .
luc:moleculeSize luc:setParam "1" .
luc:includePredicates luc:setParam "http://www.w3.org/2000/01/rdf-schema#label" .
luc:includeEntities luc:setParam wn20schema:NounSynset.
luc:nounIndex luc:createIndex "true".
}
When running the query
select * where {
{?id luc:nounIndex "credict"}
?id luc:score ?score.
}
The result is empty and I would like to get at least the word "credit" as the edit distance is 1.
Thank you!!!
If you use the ~ it should give you a fuzzy match.
Related
Any reason when creating an index the query
PREFIX elastic: <http://www.ontotext.com/connectors/elasticsearch#>
SELECT ?cntUri ?cntStr {
?cntUri elastic:listConnectors ?cntStr .
}
doesn't list it?
You can re-run the creation sparql and it reports, rightly, that you can't create it because it already exists.
So, the question is.. where is it?
For example how can I find Wikimedia Commons categories containing the string "shape" in title, using SPARQL?
Also I would like to ask how to change the script in order to:
make the search case insensitive
search whole words instead of string
search articles instead of categories
search Wikipedia elements instead of Wikimedia commons elements
Here is a basic version, using regex to filter the results to those containing "shape". For the further String functionalities you need (points 1 and 2), you should have a look here on SPARQL String functions.
Your points 3 and 4 are not clear for me, and I suggest posting a dedicated other question for them.
select distinct ?catName where {
?s wdt:P373 ?catName. # Name of the Wikimedia Commons category for ?s
Filter (regex (?catName,"shape")) # basic filtering of the results to those containg "shape"
}
I have loaded the geospatial data from geonames.org into Marklogic using RDF import.
When using the Query Console to explore the data, I see the data has been loaded into an xml document and looks like this:
<sem:triple>
<sem:subject>http://sws.geonames.org/2736540/</sem:subject>
<sem:predicate>http://www.w3.org/2003/01/geo/wgs84_pos#lat</sem:predicate>
<sem:object datatype="http://www.w3.org/2001/XMLSchema#string">40.41476</sem:object>
</sem:triple>
<sem:triple>
<sem:subject>http://sws.geonames.org/2736540/</sem:subject>
<sem:predicate>http://www.w3.org/2003/01/geo/wgs84_pos#long</sem:predicate>
<sem:object datatype="http://www.w3.org/2001/XMLSchema#string">-8.54304</sem:object>
</sem:triple>
I am able to do a SPARQL DESCRIBE and see data. Here is an example.
#prefix geonames: <http://www.geonames.org/ontology#> .
#prefix xs: <http://www.w3.org/2001/XMLSchema#> .
#prefix p0: <http://www.w3.org/2003/01/geo/wgs84_pos#> .
<http://sws.geonames.org/2736540/> geonames:parentCountry <http://sws.geonames.org/2264397/> ;
geonames:countryCode "PT"^^xs:string ;
p0:long "-8.54304"^^xs:string ;
geonames:featureCode <http://www.geonames.org/ontology#P.PPL> ;
geonames:parentADM1 <http://sws.geonames.org/2742610/> ;
geonames:parentFeature <http://sws.geonames.org/2742610/> ;
<http://www.w3.org/2000/01/rdf-schema#isDefinedBy> "http://sws.geonames.org/2736540/about.rdf"^^xs:string ;
a geonames:Feature ;
geonames:locationMap <http://www.geonames.org/2736540/pedreira-de-vilarinho.html> ;
geonames:name "Pedreira de Vilarinho"^^xs:string ;
geonames:nearbyFeatures <http://sws.geonames.org/2736540/nearby.rdf> ;
geonames:featureClass geonames:P ;
p0:lat "40.41476"^^xs:string .
I want to query over this data using SPARQL QUERY as my Query Type in a way where I can take advantage of the geospatial indexes that MarkLogic can create.
I have been having trouble with two aspects of this.
How to correctly create the geospatial indexes for the wgs84_pos#lat and wgs84_pos#long predicates?
How do I access those indexes from SPARQL QUERY?
I would like to have a sparql query that would be able to find subjects within some range of a Point.
=====================================
Followup:
After following David Ennis's Answer (Which worked nicely, thanks!) I ended up with this sample Xquery that was able to select data out of documents via geosearch and then use those IRI's in a sparql values query.
Example:
xquery version "1.0-ml";
import module namespace sem = "http://marklogic.com/semantics"
at "/MarkLogic/semantics.xqy";
let $matches := cts:search(//rdf:RDF,
cts:element-pair-geospatial-query (
fn:QName("http://www.geonames.org/ontology#","Feature"),
fn:QName("http://www.w3.org/2003/01/geo/wgs84_pos#", "lat"),
fn:QName ("http://www.w3.org/2003/01/geo/wgs84_pos#","long"),
cts:circle(10, cts:point(19.8,99.8))))
let $iris := sem:iri($matches//#rdf:about)
let $bindings := (fn:map(function($n) { map:entry("featureIRI", $n) }, $iris))
let $sparql := '
PREFIX wgs: <http://www.w3.org/2003/01/geo/wgs84_pos#>
SELECT *
WHERE {
?featureIRI wgs:lat ?lat;
wgs:long ?long.
}
'
return sem:sparql-values($sparql, $bindings)
This xquery queries the geospatial index, finds matching documents and then selects the IRI in the rdf:about attribute of the xml document.
It then maps over all of those IRIs and creates map entries that can be passed in the bindings parameter of the sem:sparql-values function.
I do not believe you can do what you want via just native SPARQL. Geospacial queries in any SPARQL implementation are extensions like geoSPARQL, Apache Jena geospacial queries etc.
My suggested approach in MarkLogic:
Insert the geonames subjects into MarkLogic as unmanaged triples (an XML or JSON document with embedded triples for each one)
In the same document, include the geo-spacial data in one of the acceptable MarkLogic formats. This essentially adds geo-spacial metadata to the triple since it is in the same fragment.
Add geo-spacial path-range-indexes for the geospacial data.
Use SPARQL inside of MarkLogic with a cts query restriction.
The Building Blocks for above:
Understanding unmanaged triples
Understanding Geo-spacial Region Types
Understanding Geo-spacial Indexes
Understanding Geo-spacial Queries
Understanding Semantics with cts search
Another approach to the final query could be the Optic API but I do not see how it would negate the need to do steps 1-3
I am trying to teach myself this weekend how to run API queries against a data source in this case data.gov. At first I thought I'd use a simple SQL variant, but it seems in this case I have to use SPARQL.
I've read through the documentation, downloaded Twinkle, and can't seem to quite get it to run. Here is an example of a query I'm running. I'm basically trying to find all gas stations that are null around Denver, CO.
PREFIX station: https://api.data.gov/nrel/alt-fuel-stations/v1/nearest.json?api_key=???location=Denver+CO
SELECT *
WHERE
{ ?x station:network ?network like "null"
}
Any help would be very much appreciated.
SPARQL is a graph pattern language for RDF triples. A query consists of a set of "basic graph patterns" described by triple patterns of the form <subject>, <predicate>, <object>. RDF defines the subject and predicate with URI's and the object is either a URI (object property) or literal (datatype or language-tagged property). Each triple pattern in a query must therefore have three entities.
Since we don't have any examples of your data, I'll provide a way to explore the data a bit. Let's assume your prefix is correctly defined, which I doubt - it will not be the REST API URL, but the URI of the entity itself. Then you can try the following:
PREFIX station: <http://api.data.gov/nrel...>
SELECT *
WHERE
{ ?s station:network ?network .
}
...setting the PREFIX to correctly represent the namespace for network. Then look at the binding for ?network and find out how they represent null. Let's say it is a string as you show. Then the query would look like:
PREFIX station: <http://api.data.gov/nrel...>
SELECT ?s
WHERE
{ ?s station:network "null" .
}
There is no like in SPARQL, but you could use a FILTER clause using regex or other string matching features of SPARQL.
And please, please, please google "SPARQL" and "RDF". There is lots of information about SPARQL, and the W3C's SPARQL 1.1 Query Language Recommendation is a comprehensive source with many good examples.
I would like to use Lucene to index/search text. The text can contain mistyped words, names, etc. What is the most simple way of getting Lucene to find a document containing
"this is Licene"
when user searches for
"Lucene"?
This is only for a demo app, so we need the most simple solution.
Lucene's fuzzy queries and based on Levenshtein edit distance.
Use a fuzzy query in the QueryParser, with syntax like:
Lucene~0.5
Or create a FuzzyQuery, passing in the maximum number of edits, something like:
Query query = new FuzzyQuery(new Term("field", "lucene"), 1);
Note: FuzzyQuery, in Lucene 4.x, does not support greater edit distances than 2.
Another option you could try is using the Lucene SpellChecker:
http://lucene.apache.org/core/6_4_0/suggest/org/apache/lucene/search/spell/SpellChecker.html
It is a out of box, and very easy to use:
SpellChecker spellchecker = new SpellChecker(spellIndexDirectory);
// To index a field of a user index:
spellchecker.indexDictionary(new LuceneDictionary(my_lucene_reader, a_field));
// To index a file containing words:
spellchecker.indexDictionary(new PlainTextDictionary(new File("myfile.txt")));
String[] suggestions = spellchecker.suggestSimilar("misspelt", 5);
By default, it is using the LevensteinDistance, but you could provide your own customized Edit Distance.