Triple

T28640072
Position Surface form Disambiguated ID Type / Status
Subject Supt. Jane Prosser E724895 entity
Predicate fictionalUniverseCountry P44462 FINISHED
Object United Kingdom NE NERFINISHED

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: United Kingdom | Statement: [Supt. Jane Prosser, fictionalUniverseCountry, United Kingdom]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalUniverseCountry
Context triple: [Supt. Jane Prosser, fictionalUniverseCountry, United Kingdom]
  • A. nationalityOfFictionalSetting
    Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
  • B. countryOfOriginFictional
    Indicates that a fictional work, character, or element originates from or is associated with a particular country within its narrative or setting.
  • C. countryOfFictionalContext chosen
    Indicates that a work of fiction is primarily set in, or contextually associated with, a particular country.
  • D. fictionalUniverseLocation
    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.
  • E. fictionalUniverse
    Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
  • 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_69f01d8328c48190bc0e5f9b9b848582 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f7b2f3a104819098ddd8909eaf596c completed May 3, 2026, 8:41 p.m.
PD Predicate disambiguation batch_69f7b1b8a9fc8190a1279e67a2d12707 completed May 3, 2026, 8:36 p.m.
Created at: April 28, 2026, 4:43 a.m.