Triple

T11764170
Position Surface form Disambiguated ID Type / Status
Subject Maria Ferres E279735 entity
Predicate associatedWithPlaceInFiction P88124 FINISHED
Object Roman salons 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: Roman salons | Statement: [Maria Ferres, associatedWithPlaceInFiction, Roman salons]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithPlaceInFiction
Context triple: [Maria Ferres, associatedWithPlaceInFiction, Roman salons]
  • A. fictionalLocationAssociatedWith
    Indicates a relationship where a fictional entity (such as a character, event, or work) is connected to or set in a particular fictional location.
  • B. associatedWithCaseInFiction
    Indicates that an entity is connected to, involved in, or relevant to a particular case or investigation within a fictional context.
  • C. hasPlaceInFiction chosen
    Indicates that a fictional work or element is associated with, set in, or takes place within a particular fictional location or setting.
  • D. locatedNearFiction
    Indicates that one fictional entity or place is situated close to another within an imagined or narrative context.
  • E. associatedWithFictionalEvent
    Indicates that an entity has a connection or involvement with a fictional event, such as being based on, inspired by, or participating in that imagined occurrence.
  • 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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a5248e0881909ed1b4df7be422f7 completed April 10, 2026, 7:22 a.m.
PD Predicate disambiguation batch_69d88a829fe481909cc5431de7d6058e completed April 10, 2026, 5:28 a.m.
Created at: April 8, 2026, 9:41 p.m.