Triple

T6137852
Position Surface form Disambiguated ID Type / Status
Subject Simon Zelotes E136879 entity
Predicate nameMeaning P453 FINISHED
Object Simon the Zealous E134727 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 the Zealous | Statement: [Simon Zelotes, nameMeaning, Simon the Zealous]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simon the Zealous
Context triple: [Simon Zelotes, nameMeaning, Simon the Zealous]
  • A. Simon the Cananaean chosen
    Simon the Cananaean is one of the Twelve Apostles of Jesus in the New Testament, traditionally identified with Simon the Zealot.
  • B. Simon
    Simon is a common masculine given name of Hebrew origin, widely used in many cultures and languages.
  • C. 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.
  • D. Simon
    Simon is a common surname of English and Jewish origin borne by numerous notable individuals across politics, business, arts, and sciences.
  • E. 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.
  • 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_69c008a179388190a3b5a081bbf46d55 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05c83aefc8190b0e250e96f2b10b4 completed March 22, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135e78950819085a2fdd7538af4cb completed March 23, 2026, 12:45 p.m.
Created at: March 22, 2026, 4:15 p.m.