Triple

T13214799
Position Surface form Disambiguated ID Type / Status
Subject Kirkwood gaps E314582 entity
Predicate namedAfter P63 FINISHED
Object Daniel Kirkwood E80098 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: Daniel Kirkwood | Statement: [Kirkwood gaps, namedAfter, Daniel Kirkwood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Kirkwood
Context triple: [Kirkwood gaps, namedAfter, Daniel Kirkwood]
  • A. Daniel Kirkwood chosen
    Daniel Kirkwood was a 19th-century American astronomer best known for discovering the Kirkwood gaps in the asteroid belt.
  • B. John Gamble Kirkwood
    John Gamble Kirkwood was an influential American theoretical chemist and physicist known for his foundational contributions to statistical mechanics and the theory of liquids.
  • C. John L. Kirk
    John L. Kirk was an English doctor and collector whose extensive assemblage of everyday historical objects led to the creation of York Castle Museum in York, England.
  • D. William M. Hartmann
    William M. Hartmann is an American physicist and psychoacoustician known for his influential research on auditory perception and acoustics.
  • E. R. K. Kirkwood
    R. K. Kirkwood is a physicist known for his contributions to plasma physics and high-energy-density science.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf28c9c819080d7b42d20f579d1 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7305a8c108190aff4e4797370f3d3 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:18 p.m.