Triple

T17244391
Position Surface form Disambiguated ID Type / Status
Subject Arthur Barrett E418583 entity
Predicate familyName P18 FINISHED
Object Barrett E199811 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: Barrett | Statement: [Arthur Barrett, familyName, Barrett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barrett
Context triple: [Arthur Barrett, familyName, Barrett]
  • A. Barrett chosen
    Barrett is a common English and Irish surname borne by numerous notable individuals across politics, law, sports, and the arts.
  • B. Barret
    Barret is the middle name of William B. Travis, the 19th-century American lawyer and commander who became a key figure in the Battle of the Alamo during the Texas Revolution.
  • C. Barrettali
    Barrettali is a small commune on the Cap Corse peninsula in Haute-Corse, Corsica, known for its rugged coastal landscape and traditional Mediterranean village character.
  • D. Barret Zoph
    Barret Zoph is a machine learning researcher known for his work on neural architecture search and contributions to deep learning at Google Brain.
  • E. Barnett
    Barnett is an English-language surname of Norman origin that has been borne by various notable figures in fields such as politics, academia, and the arts.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e22fb2c8190aea5d3872095bf46 completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170f5582c81908efb7a369a096aeb completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:39 a.m.