Triple

T17522804
Position Surface form Disambiguated ID Type / Status
Subject John Altschuler E426716 entity
Predicate coCreatorOf P806 FINISHED
Object Lopez NE NERFINISHED

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: Lopez | Statement: [John Altschuler, coCreatorOf, Lopez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lopez
Context triple: [John Altschuler, coCreatorOf, Lopez]
  • A. Lopez
    Lopez is a municipality in the province of Quezon in the Philippines, known for its agricultural economy and coastal location.
  • B. López chosen
    López is a common Spanish surname widely borne across Spain and Latin America.
  • C. Vini Lopez
    Vini Lopez is an American drummer best known as an original member of Bruce Springsteen's E Street Band, contributing to the group's early recordings and live performances.
  • D. Danny Lopez
    Danny Lopez is a former American professional boxer and world featherweight champion known for his formidable punching power and exciting, aggressive style in the ring.
  • E. Geny Lopez
    Geny Lopez was a prominent Filipino media executive best known for leading and expanding ABS-CBN into the Philippines’ largest broadcasting network.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d40ee08190b79d8e3d7f1b1272 completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.