Triple

T13002671
Position Surface form Disambiguated ID Type / Status
Subject Bravo app E322206 entity
Predicate brandExtensionOf P10460 FINISHED
Object Bravo E1031427 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: Bravo | Statement: [Bravo app, brandExtensionOf, Bravo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bravo
Context triple: [Bravo app, brandExtensionOf, Bravo]
  • A. Bravo chosen
    Bravo is a company best known for operating the Bravo app, a platform that facilitates cashless tipping and payments.
  • B. Bravo
    Bravo is an American cable television network best known for its reality TV programming and pop culture–focused entertainment.
  • C. Brava
    Brava is a small, mountainous island in the Cape Verde archipelago known for its lush vegetation, volcanic landscapes, and traditional Creole culture.
  • D. Best of the Best
    Best of the Best is a 1989 American martial arts sports drama film about a U.S. taekwondo team competing against South Korea, known for its intense tournament action and ensemble cast.
  • E. The Bravados
    The Bravados is a 1958 American Western film starring Gregory Peck as a vengeful rancher hunting down a group of escaped convicts.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9828748190b2ad9ea29180b7d3 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f716b885708190b6c38c481fa9ca21 completed May 3, 2026, 9:34 a.m.
Created at: April 9, 2026, 8:47 p.m.