Triple

T30390145
Position Surface form Disambiguated ID Type / Status
Subject Ben Affleck as Stephen Collins E773056 entity
Predicate countryRepresentedInFiction P186947 FINISHED
Object United States 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 States | Statement: [Ben Affleck as Stephen Collins, countryRepresentedInFiction, United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: countryRepresentedInFiction
Context triple: [Ben Affleck as Stephen Collins, countryRepresentedInFiction, United States]
  • A. countryOfFictionalRepresentation chosen
    Indicates that one entity is the country in which another entity (such as a work or character) is fictionally set or represented.
  • B. countryTypeInFiction
    Indicates that a country is classified according to its role or nature within a fictional context (e.g., fictional, real-but-fictionalized, alternate-history, etc.).
  • C. associatedWithCountryInFiction
    Indicates a fictional relationship in which an entity is linked or connected to a particular country within a fictional context or narrative.
  • D. nationalityOfFictionalSetting
    Indicates that a fictional setting is associated with, or belongs to, a particular nationality or country.
  • E. countryOfRegistryInFiction
    Indicates the fictional country in which an entity (such as a vehicle, vessel, or organization) is officially registered or flagged within a fictional 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_69f2248ef0a48190aa54d4d8ac3e5758 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69ff779e3f0c8190a861f1e4000fd9d9 completed May 9, 2026, 6:06 p.m.
PD Predicate disambiguation batch_69ff77202638819086e4b9f9c0bc7b31 completed May 9, 2026, 6:04 p.m.
Created at: April 29, 2026, 8:02 p.m.