Triple

T32843521
Position Surface form Disambiguated ID Type / Status
Subject Ship in a Bottle E840034 entity
Predicate featuresHolodeckCharacter P93957 FINISHED
Object Countess Regina Bartholomew 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: Countess Regina Bartholomew | Statement: [Ship in a Bottle, featuresHolodeckCharacter, Countess Regina Bartholomew]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuresHolodeckCharacter
Context triple: [Ship in a Bottle, featuresHolodeckCharacter, Countess Regina Bartholomew]
  • A. featuresCharacterWith chosen
    Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
  • B. AICharacteristics
    Indicates the defining traits, behaviors, or properties that characterize an artificial intelligence system.
  • C. featuresReturningCharacterFrom
    Indicates that a work includes the reappearance of a character who previously appeared in the referenced source work.
  • D. featuresFictionalElement
    Indicates that one entity includes, presents, or incorporates a fictional element (such as an imaginary character, place, object, or concept) as part of its content or composition.
  • E. featuresFictionalProgram
    Indicates that a work includes or presents a fictional program (such as a TV show, software, or in-universe broadcast) as part of its content.
  • 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_69f3493ff0888190b51e974eae2a7834 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_6a013f09b0988190ba3179c7d56c726a completed May 11, 2026, 2:29 a.m.
PD Predicate disambiguation batch_6a013e600e248190a1a9c363702c8586 completed May 11, 2026, 2:26 a.m.
Created at: May 1, 2026, 1:16 a.m.