Triple

T8376468
Position Surface form Disambiguated ID Type / Status
Subject Gilbert Padilla E197588 entity
Predicate givenName P17 FINISHED
Object Gilbert E88415 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: Gilbert | Statement: [Gilbert Padilla, givenName, Gilbert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gilbert
Context triple: [Gilbert Padilla, givenName, Gilbert]
  • A. Gilbert
    Gilbert is a rapidly growing suburban town in the southeastern Phoenix metropolitan area known for its family-friendly communities and high quality of life.
  • B. Gilbert chosen
    Gilbert is a masculine given name of Norman-French origin that has been borne by various notable figures, including philosophers, writers, and entertainers.
  • C. Gilbert
    Gilbert is a renowned sports equipment manufacturer best known for producing high-quality rugby balls used in major international competitions.
  • D. Niles
    Niles is the witty, sarcastic butler from the sitcom "The Nanny," known for his sharp one-liners and ongoing rivalry with C.C. Babcock.
  • E. Niles
    Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
  • 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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80c094908190afe9cc54ce4f4d58 completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde7f19ba08190a08cf5aea522c021 completed April 2, 2026, 3:52 a.m.
Created at: March 30, 2026, 6:01 p.m.