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Advanced features

SPARQL+Text and SPARQL Autocompletion

On top of the vanilla SPARQL functionality, QLever allows so-called SPARQL+Text queries on a text corpus linked to a knowledge base via entity recognition. For example, the following query finds all mentions of astronauts next to the words "moon" and "walk*" in the text corpus:

SELECT ?a TEXT(?t) SCORE(?t) WHERE {
    ?a <is-a> <Astronaut> .
    ?t ql:contains-entity ?a .
    ?t ql:contains-word "walk* moon"
} ORDER BY DESC(SCORE(?t))

Such queries can be simulated in standard SPARQL, but only with poor performance, see the CIKM'17 paper above. Details about the required input data and the SPARQL+text query syntax and semantics can be found here.

QLever also supports efficient SPARQL autocompletion. For example, the following query yields a list of all predicates associated with people in the knowledge base, ordered by the number of people which have that predicate.

SELECT ?predicate (COUNT(?predicate) as ?count) WHERE {
  ?x <is-a> <Person> .
  ?x ql:has-predicate ?predicate
}
GROUP BY ?predicate
ORDER BY DESC(?count)

Note that this query could also be processed by a standard SPARQL engine simply by replacing the second triple with ?x ?predicate ?object and adding DISTINCT inside the COUNT().

However, that query will produce a very large intermediate result (all triples of all people) with a correspondingly long query time. In contrast, the query above takes only about 100 ms on a standard Linux machine (with 16 GB memory) and a dataset with 360 million triples and 530 million text records.

Statistics:

You can get statistics for the currently active index in the following way:

<server>:<port>/?cmd=stats

This query will yield a JSON response that features:

  • The name of the KB index
  • The number of triples in the KB index
  • The number of index permutations build (usually 2 or 6)
  • The numbers of distinct subjects, predicates and objects (only available if 6 permutations are built)
  • The name of the text index (if one is present)
  • The number of text records in the text index (if a text index is present)
  • The number of word occurrences/postings in the text index (if a text index is present)
  • The number of entity occurrences/postings in the text index (if a text index is present)

The name of an index is the name of the input .nt file (and wordsfile for the text index), but can also be specified manually while building an index. Therefore, IndexbuilderMain takes two optional arguments: --text-index-name (-T) and --kb-index-name (-K).

Send vs Compute

Currently, QLever does not compute partial results if there is a LIMIT modifier.

However, strings (for entities and text excerpts) are only resolved for those items that that will be transmitted. Furthermore, a UI usually only requires a limited amount of rows at a time.

While specifying a LIMIT is recommended, some experiments may want to measure the time to produce the full result. Therefore an additional HTTP parameter &send=<x> can be used to send only k result rows while still computing the readable result for up to LIMIT rows.

IMPORTANT: Unless you want to measure QLever's performance, using LIMIT (+ OFFSET for sequential loading) is preferred in all applications. LIMIT is faster and produces the same output as the send parameter