Triple

T3069370
Position Surface form Disambiguated ID Type / Status
Subject Judith Gardenier E62182 entity
Predicate fictionalSetting P26457 FINISHED
Object village in the Catskill Mountains, New York 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: village in the Catskill Mountains, New York | Statement: [Judith Gardenier, fictionalSetting, village in the Catskill Mountains, New York]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalSetting
Context triple: [Judith Gardenier, fictionalSetting, village in the Catskill Mountains, New York]
  • A. fictionalUniverse
    Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
  • B. fictionalUniverseLocation chosen
    Indicates that one entity is a location or setting within the fictional universe to which the other entity belongs or in which it takes place.
  • C. fictionalOrigin
    Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
  • D. setInFictionalLocation
    Indicates that an event, story, or narrative takes place within a fictional or imagined location rather than a real-world setting.
  • E. fictionalResidence
    Indicates that one entity is the place where another entity lives or is based within a fictional or imaginary context.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada100f0b8819095da366fdc6803a8 completed March 8, 2026, 4:17 p.m.
PD Predicate disambiguation batch_69ad9624b7a0819091d255614f5819ea completed March 8, 2026, 3:30 p.m.
Created at: March 8, 2026, 3:02 p.m.