Triple

T20210805
Position Surface form Disambiguated ID Type / Status
Subject Horcrux E493480 entity
Predicate notableExample P1503 FINISHED
Object Harry Potter (unintended) 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: Harry Potter (unintended) | Statement: [Horcrux, notableExample, Harry Potter (unintended)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harry Potter (unintended)
Context triple: [Horcrux, notableExample, Harry Potter (unintended)]
  • A. Potter
    Potter is a masculine given name most notably borne by U.S. Supreme Court Justice Potter Stewart.
  • B. Potter
    Potter is a small town located in Yates County in the Finger Lakes region of New York State.
  • C. Potter
    Potter is the surname of Beatrix Potter, the renowned English writer, illustrator, and natural scientist best known for her children's books featuring animal characters such as Peter Rabbit.
  • D. Harry Potter chosen
    Harry Potter is a young wizard who attends Hogwarts School of Witchcraft and Wizardry and becomes famous for surviving an attack by the dark wizard Lord Voldemort.
  • E. Deconstructing Harry
    Deconstructing Harry is a 1997 dark comedy film written and directed by Woody Allen that follows a troubled writer whose fictional characters begin to intersect with his chaotic real 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66ed5691c8190bf253b1d4ee6e88f completed April 20, 2026, 6:22 p.m.
Created at: April 11, 2026, 11:38 p.m.