Triple

T32507007
Position Surface form Disambiguated ID Type / Status
Subject Catherine Hübscher E830825 entity
Predicate notableTraitInSources P201460 FINISHED
Object frank speech 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: frank speech | Statement: [Catherine Hübscher, notableTraitInSources, frank speech]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: notableTraitInSources
Context triple: [Catherine Hübscher, notableTraitInSources, frank speech]
  • A. notableTraitInFiction
    Indicates that a particular trait, characteristic, or quality is especially prominent or defining for an entity within fictional works.
  • B. hasParticularNotableCharacteristic chosen
    Indicates that an entity possesses a specific, noteworthy characteristic or quality that distinguishes it in some relevant context.
  • C. notableTraitOnStage
    Indicates that an entity is characterized by a distinctive or noteworthy trait specifically in the context of performing or appearing on stage.
  • D. notableTraitInGames
    Indicates that a particular characteristic or quality is especially prominent or well-known in the context of games.
  • E. notableCollectionCharacteristic
    Indicates that a collection is distinguished by a particular defining feature or quality that makes it notable.
  • 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_69f3492318348190ba37fb6b5f1d67f4 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_6a037c894b488190bcbec2eccaff4a01 completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a0379edf2d88190b492fca86ed23cac completed May 12, 2026, 7:05 p.m.
Created at: May 1, 2026, 1 a.m.