Triple

T33771567
Position Surface form Disambiguated ID Type / Status
Subject Veronica Mitchell E865394 entity
Predicate hasSiblingInFiction P98560 FINISHED
Object Roxy Mitchell 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: Roxy Mitchell | Statement: [Veronica Mitchell, hasSiblingInFiction, Roxy Mitchell]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSiblingInFiction
Context triple: [Veronica Mitchell, hasSiblingInFiction, Roxy Mitchell]
  • A. hasChildInFiction
    Indicates that a fictional work or character includes another character as their child within the fictional narrative.
  • B. hasFictionalSibling
    Indicates that one entity is a fictional character who is a sibling of another entity.
  • C. hasSiblingInStory chosen
    Indicates that one character in a narrative has at least one sibling who also appears within the same story.
  • D. hasRelativeInFiction
    Indicates that one entity has a relative or family member who appears as a character within a fictional work associated with the other entity.
  • E. hasAssociatedWorkOfFiction
    Indicates that an entity is linked to a related work of fiction, such as a novel, film, or story that is associated with it.
  • F. None of above.

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_69f3498df6f88190bf9647ea4e4a956e completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69fd6dbd1b648190b1a0b391c03aebc5 completed May 8, 2026, 4:59 a.m.
PD Predicate disambiguation batch_69fd6a9020548190bbfa845360ac85fb completed May 8, 2026, 4:46 a.m.
Created at: May 1, 2026, 1:45 a.m.