Triple

T23480342
Position Surface form Disambiguated ID Type / Status
Subject Captain Clarence Oveur E570386 entity
Predicate worksOnRouteInFiction P131086 FINISHED
Object Los Angeles to Chicago flight 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: Los Angeles to Chicago flight | Statement: [Captain Clarence Oveur, worksOnRouteInFiction, Los Angeles to Chicago flight]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: worksOnRouteInFiction
Context triple: [Captain Clarence Oveur, worksOnRouteInFiction, Los Angeles to Chicago flight]
  • A. workInFiction
    Indicates that one entity is a fictional work in which the other entity appears or is set.
  • B. worksInFictionalContext chosen
    Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
  • C. worksForInNovel
    Indicates that one entity is employed by or serves another entity within the fictional context of a specific novel.
  • D. eraWithinFiction
    Indicates that a time period or era exists inside the narrative world or timeline of a fictional work.
  • E. flowsThroughInFiction
    Indicates that, within a fictional context or narrative, one entity (typically a river or similar medium) passes through, traverses, or courses across another entity (such as a location or region).
  • 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_69e245af8a88819084f2704f6d265a92 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a74f48d8819080e875aaea8b46b3 completed April 29, 2026, 6:38 a.m.
PD Predicate disambiguation batch_69f0620ac3608190b36916261ea50f54 completed April 28, 2026, 7:30 a.m.
Created at: April 17, 2026, 6:03 p.m.