Triple

T2467185
Position Surface form Disambiguated ID Type / Status
Subject University of São Paulo E55278 entity
Predicate hasCampus P116 FINISHED
Object Santos E89307 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: Santos | Statement: [University of São Paulo, hasCampus, Santos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santos
Context triple: [University of São Paulo, hasCampus, Santos]
  • A. Santos chosen
    Santos is a major Brazilian port city on the coast of São Paulo state, known for its extensive coffee export history and popular beachfront.
  • B. Santos
    Santos is a common Portuguese surname shared by numerous notable figures in politics, sports, and the arts across Portuguese-speaking countries.
  • C. Nova Cruz
    Nova Cruz is a municipality in the Brazilian state of Rio Grande do Norte, known as a regional commercial and service center in the Agreste Potiguar area.
  • D. De Rosario
    De Rosario is the surname of Dwayne De Rosario, a prominent Canadian former professional soccer player known for his goal-scoring and playmaking in Major League Soccer.
  • E. Gamboa
    Gamboa is a small town in Panama best known for its location along the Panama Canal and its proximity to the surrounding rainforest and canal infrastructure.
  • 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_69ab49e3622c8190ad22afa2c4fbb807 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd13310a8819095fd70672f933aa3 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af179f90e881909c09edb961b13a75 completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:44 p.m.