Triple

T12727062
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Region of Salvador E304133 entity
Predicate hasLargestCity P235 FINISHED
Object Salvador E543781 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: Salvador | Statement: [Metropolitan Region of Salvador, hasLargestCity, Salvador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salvador
Context triple: [Metropolitan Region of Salvador, hasLargestCity, Salvador]
  • A. Salvador
    "Salvador" is a 1986 political drama film directed by Oliver Stone, in which James Woods delivers an acclaimed performance as a cynical journalist covering the Salvadoran Civil War.
  • B. Salvador
    Salvador is a metro station on Line 1 of the Santiago Metro in Santiago, Chile.
  • C. Salvador chosen
    Salvador is a historic coastal city in northeastern Brazil known for its Afro-Brazilian culture, colonial architecture, and vibrant Carnival celebrations.
  • D. Salvador
    Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
  • E. São Salvador do Mundo
    São Salvador do Mundo is a municipality on Santiago Island in Cape Verde, known for its rural communities and mountainous inland landscapes.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96415ebe48190ae935bc3a9b00f65 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b8c84308190b57d3b5b04bb4a78 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:25 p.m.