Triple

T17963837
Position Surface form Disambiguated ID Type / Status
Subject Simon Rattle E449150 entity
Predicate givenName P17 FINISHED
Object Simon NE NERFINISHED

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: Simon | Statement: [Simon Rattle, givenName, Simon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simon
Context triple: [Simon Rattle, givenName, Simon]
  • A. Simon chosen
    Simon is a common surname of English and Jewish origin borne by numerous notable individuals across politics, business, arts, and sciences.
  • B. Simon
    Simon is a sleazy used-car salesman and comic-relief character in the action-comedy film "True Lies," who pretends to be a secret agent to seduce women.
  • C. Simon
    Simon is the young, initially timid but ultimately heroic protagonist of the anime series Tengen Toppa Gurren Lagann, known for piloting powerful mecha and embodying themes of growth and determination.
  • D. Simon
    Simon was one of the nuclear test detonations conducted during the U.S. Operation Upshot–Knothole series in 1953.
  • E. Simon
    Simon is the drag performer alter ego behind Lola in the musical and film "Kinky Boots," revealing the character’s offstage identity and personal life.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b135cd2c8190a6190cf6611dbe08 completed April 19, 2026, 10:40 a.m.
Created at: April 10, 2026, 10:22 a.m.