Triple

T30503331
Position Surface form Disambiguated ID Type / Status
Subject Sarah Kidd E776197 entity
Predicate fictionalDepictions P191964 FINISHED
Object portrayed in works about Captain Kidd 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: portrayed in works about Captain Kidd | Statement: [Sarah Kidd, fictionalDepictions, portrayed in works about Captain Kidd]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalDepictions
Context triple: [Sarah Kidd, fictionalDepictions, portrayed in works about Captain Kidd]
  • A. hasFictionalDepictions chosen
    Indicates that an entity is represented or portrayed in one or more fictional works or narratives.
  • B. portraysFictionalized
    Indicates that one entity represents or depicts another entity in a fictionalized or altered manner, rather than as a strictly accurate portrayal.
  • C. fictionalOrigin
    Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
  • D. fictionalizationOf
    Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
  • E. fictionalFocus
    Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
  • 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_69f22498c5d481908aaea89e6fab8280 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69fd32848ea88190a71e6df402bbb30e completed May 8, 2026, 12:47 a.m.
PD Predicate disambiguation batch_69fd2d7e95588190991d5f21e25155df completed May 8, 2026, 12:25 a.m.
Created at: April 29, 2026, 8:15 p.m.