Triple

T12174003
Position Surface form Disambiguated ID Type / Status
Subject Jonathan David E290042 entity
Predicate memberOfSportsTeam P330 FINISHED
Object K.A.A. Gent E185151 NE FINISHED

How this triple was built (2 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: K.A.A. Gent | Statement: [Jonathan David, memberOfSportsTeam, K.A.A. Gent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: K.A.A. Gent
Context triple: [Jonathan David, memberOfSportsTeam, K.A.A. Gent]
  • A. KAA Gent chosen
    KAA Gent is a Belgian professional football club based in Ghent, known for competing in the country’s top division and developing notable players such as Kevin De Bruyne.
  • B. MSK Gent
    MSK Gent is a prominent art museum in Ghent, Belgium, renowned for its extensive collection of Flemish and European fine arts spanning the Middle Ages to the 20th century.
  • C. Royal Antwerp F.C.
    Royal Antwerp F.C. is a historic Belgian professional football club based in Antwerp and one of the oldest clubs in the country.
  • D. KRC Genk
    KRC Genk is a Belgian professional football club known for developing top talents, including Kevin De Bruyne, and competing in the country’s top division.
  • E. Lokeren
    Lokeren is a Belgian city known for its textile and food industries, located in the province of East Flanders between Ghent and Antwerp.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915dab42881908e2580c631d4d1cf completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6a9482481909500c216f23fceb4 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:50 p.m.