Triple

T9839170
Position Surface form Disambiguated ID Type / Status
Subject "Z3: An Efficient SMT Solver" E239177 entity
Predicate authors P63068 FINISHED
Object Leonardo de Moura E46384 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: Leonardo de Moura | Statement: ["Z3: An Efficient SMT Solver", authors, Leonardo de Moura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonardo de Moura
Context triple: ["Z3: An Efficient SMT Solver", authors, Leonardo de Moura]
  • A. Leonardo de Moura chosen
    Leonardo de Moura is a Brazilian computer scientist best known for creating the Z3 theorem prover and contributing significantly to automated reasoning and formal verification.
  • B. André Lara Resende
    André Lara Resende is a Brazilian economist known as one of the principal architects of Brazil’s 1990s economic stabilization and currency reform.
  • C. Luis Martínez-Feduchi
    Luis Martínez-Feduchi was a Spanish architect known for his influential early 20th-century modernist works in Madrid.
  • D. Daniel Rezende
    Daniel Rezende is a Brazilian film editor best known for his acclaimed work on internationally recognized films such as "City of God" and other major cinematic projects.
  • E. Euclides Pinto Martins
    Euclides Pinto Martins was a pioneering Brazilian aviator known for his early long-distance flights and contributions to the development of aviation in Brazil.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34921b881909836ba0f5b42a27b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1ead061388190abbed7eb29e8ea52 completed April 5, 2026, 4:53 a.m.
Created at: March 30, 2026, 8:33 p.m.