Triple

T11390196
Position Surface form Disambiguated ID Type / Status
Subject Pope Martin IV E269815 entity
Predicate givenName P17 FINISHED
Object Simon E449149 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: Simon | Statement: [Pope Martin IV, givenName, Simon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simon
Context triple: [Pope Martin IV, givenName, Simon]
  • A. Simon
    Simon is the given name of Simon Bolivar Buckner Jr., a U.S. Army lieutenant general who was killed in action while commanding forces during the Battle of Okinawa in World War II.
  • B. Simon
    Simon is a common surname of English and Jewish origin borne by numerous notable individuals across politics, business, arts, and sciences.
  • C. Simon chosen
    Simon is a common masculine given name of Hebrew origin, widely used in many cultures and languages.
  • D. Simon
    Simon is the central character in Ang Lee's 1993 film "The Wedding Banquet," a Taiwanese American man who enters a sham marriage to appease his traditional parents while secretly living with his male partner in New York.
  • E. 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.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d800160a1c81909d115bf89fe54a49 completed April 9, 2026, 7:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58c672da48190affacc0f19ef0c7a completed April 20, 2026, 2:16 a.m.
Created at: April 8, 2026, 9:34 p.m.