Triple

T20662092
Position Surface form Disambiguated ID Type / Status
Subject The Institute E507781 entity
Predicate hasMotiveOfAntagonists P108466 FINISHED
Object preventing global catastrophes through unethical means 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: preventing global catastrophes through unethical means | Statement: [The Institute, hasMotiveOfAntagonists, preventing global catastrophes through unethical means]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMotiveOfAntagonists
Context triple: [The Institute, hasMotiveOfAntagonists, preventing global catastrophes through unethical means]
  • A. hasMotiveOfCriminals
    Indicates that the specified motive is attributed to or associated with the criminals in question.
  • B. missionOfAntagonist chosen
    Indicates the primary goal, plan, or objective that the antagonist is actively pursuing.
  • 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_69e0b4c059bc81908ea762cd73ea4424 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b2f2ee4081908df9ba897c9dfc98 completed April 20, 2026, 11:12 p.m.
PD Predicate disambiguation batch_69e5c0315f5081908098707c6455e56e completed April 20, 2026, 5:57 a.m.
Created at: April 16, 2026, 11:44 a.m.