Triple

T20603341
Position Surface form Disambiguated ID Type / Status
Subject Juliet’s Balcony E506237 entity
Predicate hasFictionVsRealityStatus P29186 FINISHED
Object fictional association with Juliet’s home 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 association with Juliet’s home | Statement: [Juliet’s Balcony, hasFictionVsRealityStatus, fictional association with Juliet’s home]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFictionVsRealityStatus
Context triple: [Juliet’s Balcony, hasFictionVsRealityStatus, fictional association with Juliet’s home]
  • A. fictionalStatus
    Indicates that an entity exists only in imagination or narrative and does not correspond to a real-world counterpart.
  • B. hasRelativeInFiction
    Indicates that one entity has a relative or family member who appears as a character within a fictional work associated with the other entity.
  • C. hasFictionComponent
    Indicates that something includes, contains, or is composed in part of a fictional element or work.
  • D. realityStatus chosen
    Indicates the relationship between an entity and its state of existence or authenticity within a given context or world (e.g., real, fictional, hypothetical, simulated).
  • E. hasViewOfFictional
    Indicates that one entity has a visual or conceptual perspective of a fictional entity or scene.
  • 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_69e0b4bb2b4081908fa4a72444120f35 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aa22663881909a8d4644e1c48dc2 completed April 20, 2026, 10:35 p.m.
PD Predicate disambiguation batch_69e59fffe1748190825e4eaa90340631 completed April 20, 2026, 3:39 a.m.
Created at: April 16, 2026, 11:41 a.m.