Triple

T17911039
Position Surface form Disambiguated ID Type / Status
Subject Sailor Moon E447818 entity
Predicate hasSequelAnime P1961 FINISHED
Object Sailor Moon R 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: Sailor Moon R | Statement: [Sailor Moon, hasSequelAnime, Sailor Moon R]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sailor Moon R
Context triple: [Sailor Moon, hasSequelAnime, Sailor Moon R]
  • A. Sailor Moon chosen
    Sailor Moon is a popular Japanese magical girl anime and manga series that follows schoolgirl Usagi Tsukino as she transforms into a superheroine to fight evil and protect the world with her fellow Sailor Guardians.
  • B. Sailor King
    Sailor King is the popular nickname of William IV of the United Kingdom, reflecting his long naval career before becoming king.
  • C. Sailor Beware!
    Sailor Beware! is a popular mid-20th-century British stage comedy best known for its humorous portrayal of working-class life and romantic entanglements.
  • D. Ranma ½
    Ranma ½ is a popular Japanese manga and anime series by Rumiko Takahashi that blends martial arts action with gender-bending comedy and romantic entanglements.
  • E. Sailor Beware
    Sailor Beware is a 1952 American comedy film featuring the popular comic duo Dean Martin and Jerry Lewis in a Navy-themed romp.
  • 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_69d8b9f6d394819082a6d69fd1e23d2f completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49ea017d081908be850a39edf601f completed April 19, 2026, 9:21 a.m.
Created at: April 10, 2026, 10:19 a.m.