Triple

T12739413
Position Surface form Disambiguated ID Type / Status
Subject Bornova E304448 entity
Predicate hasPublicTransportConnectionTo P3791 FINISHED
Object Buca E696150 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: Buca | Statement: [Bornova, hasPublicTransportConnectionTo, Buca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buca
Context triple: [Bornova, hasPublicTransportConnectionTo, Buca]
  • A. Buca
    Buca was an ancient town of the Frentani people in central Italy, known as one of their principal settlements.
  • B. Buca chosen
    Buca is a large district of İzmir in western Turkey, known as a residential and university area within the metropolitan region.
  • C. Vucciria
    Vucciria is a historic market district in Palermo, Sicily, famed for its bustling street life, traditional food stalls, and vibrant local culture.
  • D. Maria and Enzo's Ristorante
    Maria and Enzo's Ristorante is an Italian-themed restaurant known for its classic cuisine and vintage aviation-inspired decor, located at Disney Springs in Walt Disney World Resort.
  • E. Trattoria al Forno
    Trattoria al Forno is an Italian-inspired restaurant at Walt Disney World known for its rustic cuisine and character dining experiences.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9646dfc908190bc398935d1d23537 completed April 10, 2026, 8:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b8c84308190b57d3b5b04bb4a78 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:26 p.m.