Triple

T23992012
Position Surface form Disambiguated ID Type / Status
Subject Intensity E605089 entity
Predicate hasMotiveOfAntagonist P65261 FINISHED
Object pursuit of intense experiences and sensations 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: pursuit of intense experiences and sensations | Statement: [Intensity, hasMotiveOfAntagonist, pursuit of intense experiences and sensations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMotiveOfAntagonist
Context triple: [Intensity, hasMotiveOfAntagonist, pursuit of intense experiences and sensations]
  • A. missionOfAntagonist
    Indicates the primary goal, plan, or objective that the antagonist is actively pursuing.
  • B. hasMotiveOfCriminals chosen
    Indicates that the specified motive is attributed to or associated with the criminals in question.
  • C. hasAntagonisticProtagonist
    Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
  • D. antagonistActionOf
    Indicates that one entity performs an action in opposition or hostility toward another entity, acting as its antagonist.
  • E. antagonistOf
    Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
  • 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_69e295463f7c8190b1c19dbd114641b9 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d38c28d48190937660529bbced19 completed April 29, 2026, 9:46 a.m.
PD Predicate disambiguation batch_69f1615994c48190a5de95d3f7e5cd0a completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 9:37 p.m.