Triple

T3799073
Position Surface form Disambiguated ID Type / Status
Subject John Austin E91643 entity
Predicate name P16 FINISHED
Object John Austin E91643 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: John Austin | Statement: [John Austin, name, John Austin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Austin
Context triple: [John Austin, name, John Austin]
  • A. John Austin chosen
    John Austin was a 19th-century English legal theorist best known for developing the theory of legal positivism, which distinguishes law as it is from law as it ought to be.
  • B. John Finnis
    John Finnis is a prominent legal philosopher best known for his work on natural law theory and his influential book "Natural Law and Natural Rights."
  • C. John C. Austin
    John C. Austin was a prominent early 20th-century American architect known for shaping the civic and cultural landscape of Los Angeles through several landmark buildings.
  • D. Ronald Dworkin
    Ronald Dworkin was a prominent American legal and political philosopher known for his theory of law as integrity and his influential work on rights, equality, and constitutional interpretation.
  • E. John P.N. Austin
    John P.N. Austin is an American educator who has served as the head of school at the prestigious Deerfield Academy in Massachusetts.
  • 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_69aed96354f48190a768966d6bd19b04 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7a43c408190a54cff649f63e69f completed March 9, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f064471881908b52b2f64e50a83d completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:15 p.m.