Triple

T16380035
Position Surface form Disambiguated ID Type / Status
Subject João Tavares E397778 entity
Predicate hasFamilyName P18 FINISHED
Object Tavares E79684 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: Tavares | Statement: [João Tavares, hasFamilyName, Tavares]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tavares
Context triple: [João Tavares, hasFamilyName, Tavares]
  • A. Tavares chosen
    Tavares is a Portuguese surname borne by numerous notable individuals across fields such as business, sports, and the arts.
  • B. Conley
    Conley is a surname most prominently associated with NBA point guard Mike Conley Jr.
  • C. Tolan
    Tolan is a surname most notably associated with American television producer, writer, and director Peter Tolan.
  • D. Toland
    Toland is a surname most notably associated with Gregg Toland, the pioneering American cinematographer renowned for his innovative deep-focus techniques in films like "Citizen Kane."
  • E. Dantley
    Dantley is a surname most prominently associated with Adrian Dantley, a Hall of Fame American professional basketball player known for his prolific scoring in the NBA.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319db5b648190a8fca23518a1fb39 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035689ef08190ba980a359498ca56 completed May 10, 2026, 7:36 a.m.
Created at: April 10, 2026, 5:08 a.m.