Triple

T6079806
Position Surface form Disambiguated ID Type / Status
Subject STS-58 E135492 entity
Predicate missionSpecialist P21471 FINISHED
Object David A. Wolf E331959 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: David A. Wolf | Statement: [STS-58, missionSpecialist, David A. Wolf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David A. Wolf
Context triple: [STS-58, missionSpecialist, David A. Wolf]
  • A. David Wolf chosen
    David Wolf is an American astronaut and physician known for his long-duration missions aboard the Russian Mir space station and the International Space Station.
  • B. Alexander L. Wolf
    Alexander L. Wolf is a prominent computer scientist known for his influential contributions to software engineering and distributed systems research.
  • C. Daniel A. Wolf
    Daniel A. Wolf is an American entrepreneur and politician best known as the founder of regional airline Cape Air and as a former Massachusetts state senator.
  • D. Roland A. Madden
    Roland A. Madden is an atmospheric scientist best known for co-identifying the Madden–Julian Oscillation, a major pattern of tropical intraseasonal climate variability.
  • E. Roger K. Furse
    Roger K. Furse was a British costume and production designer renowned for his work on classic films, including being among the earliest recipients of the Academy Award for Best Costume Design.
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0577209b88190afe5b1365cf6436d completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1252a178c81909a3d689ad748fb5e completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:11 p.m.