Triple

T505331
Position Surface form Disambiguated ID Type / Status
Subject St. Petersburg, Missouri E10490 entity
Predicate fictionalStatus P14491 FINISHED
Object fictional 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: fictional | Statement: [St. Petersburg, Missouri, fictionalStatus, fictional]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalStatus
Context triple: [St. Petersburg, Missouri, fictionalStatus, fictional]
  • A. fictionalizationOf
    Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
  • B. fictionalUniverseCreated
    Indicates that one entity is the creator or originator of a particular fictional universe or setting in which stories or works take place.
  • C. fictionalUniverse
    Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
  • D. hasMetafictionalRole
    Indicates that an entity plays a role within a story that self-consciously comments on, references, or breaks the conventions of fiction itself.
  • E. authorshipStatus
    Indicates the current state or condition of an entity’s role as an author in relation to a work (e.g., confirmed, disputed, anonymous, or pending).
  • F. None of above. chosen

Provenance (4 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_69a2e848adf881908e5e04f7af030093 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f14b2acc8190818e8a53eac69c54 completed Feb. 28, 2026, 1:44 p.m.
PD Predicate disambiguation batch_69a2edfce7a08190a408bc019de60d5d completed Feb. 28, 2026, 1:30 p.m.
PDg Predicate description generation batch_69a2eebbd70481908b462296671de67b completed Feb. 28, 2026, 1:33 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.