Triple

T34062197
Position Surface form Disambiguated ID Type / Status
Subject Jellaby E873520 entity
Predicate humorContribution P63937 FINISHED
Object adds humor through interactions with other characters 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: adds humor through interactions with other characters | Statement: [Jellaby, humorContribution, adds humor through interactions with other characters]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: humorContribution
Context triple: [Jellaby, humorContribution, adds humor through interactions with other characters]
  • A. humorSetting
    Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
  • B. humorSource chosen
    Indicates that one entity is the origin or cause of humor experienced in relation to another entity.
  • C. hasHumorFunction
    Indicates that something serves a humorous role or purpose, such as eliciting amusement, laughter, or comedic effect.
  • D. usedForHumor
    Indicates that something is employed with the intention of being funny, amusing, or comical.
  • E. humorousTone
    Indicates that the related communication, expression, or interaction is characterized by humor, playfulness, or comedic intent.
  • 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_69f349a4af208190afa14888f9c9fb9d completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70b9d235881908d6f8c60dfc73fc1 completed May 3, 2026, 8:47 a.m.
PD Predicate disambiguation batch_69f70ac0170c819098e3b8e41d02efef completed May 3, 2026, 8:43 a.m.
Created at: May 1, 2026, 1:52 a.m.