Triple

T7115518
Position Surface form Disambiguated ID Type / Status
Subject OBDA systems E165807 entity
Predicate typicalQueryLanguage P42338 FINISHED
Object SPARQL E29603 NE FINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: SPARQL | Statement: [OBDA systems, typicalQueryLanguage, SPARQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SPARQL
Context triple: [OBDA systems, typicalQueryLanguage, SPARQL]
  • A. SPARQL chosen
    SPARQL is a semantic query language and protocol used to retrieve and manipulate data stored in Resource Description Framework (RDF) format on the Semantic Web.
  • B. OWL 2 QL
    OWL 2 QL is a lightweight profile of the Web Ontology Language designed to enable efficient query answering over large datasets using standard relational database technologies.
  • C. RDF
    RDF (Resource Description Framework) is a standard model for data interchange on the Web that represents information as subject–predicate–object triples to enable structured, machine-readable metadata and knowledge graphs.
  • D. OWL
    OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
  • E. SHACL
    SHACL is a W3C standard language for validating RDF data against a set of constraints or shapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalQueryLanguage
Context triple: [OBDA systems, typicalQueryLanguage, SPARQL]
  • A. typicalTerm
    Indicates that something is a standard, representative, or characteristic term typically associated with a given concept or context.
  • B. numberOfQueries
    Indicates the total count of queries associated with or performed in a given context or entity.
  • C. typicalMatchType
    Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
  • D. typicalLanguages chosen
    Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
  • E. typicalIn
    Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
  • F. None of above.

Provenance (4 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c6888227bc8190a1394679e3116f90 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e5f401b881909ef4c2ab1e0750db completed March 27, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a32870e481909472f8fcd2501289 completed March 28, 2026, 9:45 a.m.
PD Predicate disambiguation batch_69c6e1c4f9788190830288d00cc37026 completed March 27, 2026, 8 p.m.
Created at: March 27, 2026, 2:43 p.m.