Triple

T6600293
Position Surface form Disambiguated ID Type / Status
Subject Orange County Convention Center E148979 entity
Predicate locatedIn P40 FINISHED
Object Orlando, Florida E11265 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: Orlando, Florida | Statement: [Orange County Convention Center, locatedIn, Orlando, Florida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orlando, Florida
Context triple: [Orange County Convention Center, locatedIn, Orlando, Florida]
  • A. Orlando chosen
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • B. Orlando
    Orlando is a common Italian surname borne by numerous individuals, including notable political and cultural figures.
  • C. Orlando
    Orlando is the young, virtuous, and romantically idealistic hero of Shakespeare’s comedy "As You Like It," known for his love for Rosalind and his conflict with his elder brother.
  • D. Orlando
    Orlando is the Italian literary counterpart of the medieval knight Roland, best known as the chivalric hero of epic poems such as "Orlando Furioso."
  • E. Orlando
    Orlando is a historic township area within Soweto, South Africa, known for its central role in the anti-apartheid struggle and vibrant local culture.
  • 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_69c687eaa7508190bb58ce2aa02039b3 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aef36b308190a172f0396e337309 completed March 27, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712841eb4819098057a290520254e completed March 27, 2026, 11:28 p.m.
Created at: March 27, 2026, 1:56 p.m.