Triple

T25752397
Position Surface form Disambiguated ID Type / Status
Subject The Brothers E648500 entity
Predicate examinesInfluenceOn P104608 FINISHED
Object U.S. foreign policy decision-making 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: U.S. foreign policy decision-making | Statement: [The Brothers, examinesInfluenceOn, U.S. foreign policy decision-making]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: examinesInfluenceOn
Context triple: [The Brothers, examinesInfluenceOn, U.S. foreign policy decision-making]
  • A. examinesImpactOn
    Indicates that one entity studies, evaluates, or analyzes the effects or consequences that another entity has on a specified subject or outcome.
  • B. exploresInfluence chosen
    Indicates that one entity investigates, examines, or analyzes the impact or effect that another entity has.
  • C. incorporatesInfluence
    Indicates that one entity integrates or absorbs the influence, ideas, or characteristics of another into itself.
  • D. influencesThrough
    Indicates that one entity affects or alters another entity indirectly by means of an intermediate factor, channel, or mechanism.
  • E. influencedIn
    Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
  • 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_69e7ab314d788190b3abe19e114080e1 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fd7fe0908190904d919f24df7e97 completed May 2, 2026, 1:34 p.m.
PD Predicate disambiguation batch_69f4938262ac8190b41f922d0407d272 completed May 1, 2026, 11:50 a.m.
Created at: April 22, 2026, 4:36 a.m.