Triple

T23845819
Position Surface form Disambiguated ID Type / Status
Subject Station Eleven E591116 entity
Predicate hasFictionalWorkWithinWork P106268 FINISHED
Object Station Eleven comic book LITERAL 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: Station Eleven comic book | Statement: [Station Eleven, hasFictionalWorkWithinWork, Station Eleven comic book]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFictionalWorkWithinWork
Context triple: [Station Eleven, hasFictionalWorkWithinWork, Station Eleven comic book]
  • A. hasFictionalWork
    Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
  • B. hasAssociatedWorkOfFiction chosen
    Indicates that an entity is linked to a related work of fiction, such as a novel, film, or story that is associated with it.
  • C. hasFictionalFilmWithinPlay
    Indicates that within a theatrical play, there is a fictional film that exists or is depicted as part of the play’s narrative or structure.
  • D. usedInFictionalWork
    Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
  • E. worksInFictionalContext
    Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
  • 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_69e25d1de32c8190a907afe9c3d6cd6d completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c88b59688190922d6bf329f08721 completed April 29, 2026, 8:59 a.m.
PD Predicate disambiguation batch_69f1614612b481908c45d99e588882f9 completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 8:09 p.m.