Triple

T5292245
Position Surface form Disambiguated ID Type / Status
Subject Hero E119767 entity
Predicate relatedWork P37 FINISHED
Object The Magic E125813 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: The Magic | Statement: [Hero, relatedWork, The Magic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Magic
Context triple: [Hero, relatedWork, The Magic]
  • A. The Magic chosen
    The Magic is a self-help book by Rhonda Byrne that expands on the themes of The Secret by focusing on the transformative power of gratitude.
  • B. El Mago
    El Mago is the nickname of Argentine former professional tennis player Guillermo Coria, renowned for his exceptional clay-court skills and speed.
  • C. La Maga
    La Maga is a mysterious, free-spirited woman who embodies emotional intuition and existential uncertainty in Julio Cortázar’s novel "Rayuela" ("Hopscotch").
  • D. The Wizard
    The Wizard is the famous nickname of Hall of Fame shortstop Ozzie Smith, renowned for his exceptional defensive skills and acrobatic plays in Major League Baseball.
  • E. The Wizard
    The Wizard is the enigmatic and ultimately humbug ruler of the Emerald City in L. Frank Baum’s classic tale "The Wizard of Oz."
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eccac481908ba3fe28c3908d1d completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21b22be08190ad5d3d6b12b80bcb completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:52 p.m.