Triple

T16389457
Position Surface form Disambiguated ID Type / Status
Subject Lewis MacDougall E398011 entity
Predicate performanceIn P6103 FINISHED
Object Pan E1158959 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: Pan | Statement: [Lewis MacDougall, performanceIn, Pan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pan
Context triple: [Lewis MacDougall, performanceIn, Pan]
  • A. Pan
    Pan is the rustic Greek god of shepherds, flocks, and wild nature, often depicted with goat-like features and associated with music and untamed wilderness.
  • B. Pan
    Pan is a genus of great apes that includes chimpanzees and bonobos, our closest living evolutionary relatives.
  • C. Pan
    Pan is a 1894 novel by Norwegian author Knut Hamsun, known for its lyrical portrayal of nature and its psychologically intense depiction of love and jealousy.
  • D. Pan
    Pan is a former member of the American rock band Black Veil Brides, known for their theatrical style and blend of glam metal and post-hardcore.
  • E. Pan chosen
    Pan is a 2015 fantasy adventure film that serves as an origin story for J.M. Barrie’s Peter Pan, reimagining how the boy who wouldn’t grow up first came to Neverland.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e326414f44819093ebc11f1b63444c completed April 18, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c58280081908e4d73a75b09dbb8 completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:08 a.m.