Triple

T11020106
Position Surface form Disambiguated ID Type / Status
Subject Stardust E260465 entity
Predicate mainCharacter P1183 FINISHED
Object Yvaine E625851 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: Yvaine | Statement: [Stardust, mainCharacter, Yvaine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yvaine
Context triple: [Stardust, mainCharacter, Yvaine]
  • A. Yvaine chosen
    Yvaine is the fallen star and central heroine of Neil Gaiman’s fantasy novel (and its film adaptation) "Stardust," whose journey intertwines magic, romance, and adventure.
  • B. Tiphaine
    Tiphaine is a French given name, notably borne by Tiphaine Auzière, the daughter of Brigitte Macron.
  • C. Marzelline
    Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
  • D. Rainelle
    Rainelle is a small town located in western Greenbrier County, West Virginia, historically tied to the lumber industry and the surrounding Appalachian region.
  • E. Viviane
    Viviane is a legendary enchantress of Arthurian romance, often identified as the Lady of the Lake and known for her role in mentoring and imprisoning the wizard Merlin.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797baad408190a53fd6941a750f68 completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e374e550508190aa3779191196f329 completed April 18, 2026, 12:11 p.m.
Created at: April 8, 2026, 9:25 p.m.