Triple

T9148758
Position Surface form Disambiguated ID Type / Status
Subject Craig Barrett E219527 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: [Craig Barrett, familyName, Barrett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barrett
Context triple: [Craig 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. 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.
  • D. 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.
  • E. Barnett
    Barnett is a masculine given name most notably associated with the influential American abstract expressionist painter Barnett Newman.
  • 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_69ca83e121dc81909912bd66953081c5 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca91a1fd08190a5bb3d9280439b09 completed April 1, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d04833858081909b616325f0e6f787 completed April 3, 2026, 11:07 p.m.
Created at: March 30, 2026, 7:20 p.m.