Triple

T6953172
Position Surface form Disambiguated ID Type / Status
Subject Stoolbend Hospital E161175 entity
Predicate hasFictionalSettingType P71478 FINISHED
Object urban hospital 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: urban hospital | Statement: [Stoolbend Hospital, hasFictionalSettingType, urban hospital]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFictionalSettingType
Context triple: [Stoolbend Hospital, hasFictionalSettingType, urban hospital]
  • A. hasFictionalLocation
    Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
  • B. hasFictionalEstablishmentType chosen
    Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
  • C. hasFictionalUniverseElement
    Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
  • D. hasFictionalUniverseGenre
    Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
  • E. hasFictionalProductionType
    Indicates that an entity is associated with a specific type or category of fictional production (such as a genre, format, or style).
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dacca12481908942ba793a104cc3 completed March 27, 2026, 7:30 p.m.
PD Predicate disambiguation batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 completed March 27, 2026, 7:17 p.m.
Created at: March 27, 2026, 2:29 p.m.