Triple

T1411935
Position Surface form Disambiguated ID Type / Status
Subject African Monetary Union E31823 entity
Predicate potentialBenefits P2188 FINISHED
Object reduced transaction costs in intra-African trade 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: reduced transaction costs in intra-African trade | Statement: [African Monetary Union, potentialBenefits, reduced transaction costs in intra-African trade]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: potentialBenefits
Context triple: [African Monetary Union, potentialBenefits, reduced transaction costs in intra-African trade]
  • A. benefits
    Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
  • B. primaryBenefit
    Indicates that one entity serves as the main or most important advantage, gain, or positive outcome associated with another entity.
  • C. hasBenefit chosen
    Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
  • D. exclusiveBenefit
    Indicates that a benefit is provided to one party or group in a way that excludes others from receiving the same advantage.
  • E. benefitForm
    Indicates that one entity is a specific form, type, or variant in which a benefit is provided or realized for another entity.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c3e3383c81909acb9c6c1c3b817a completed March 1, 2026, 10:55 p.m.
PD Predicate disambiguation batch_69a4bf048b648190ab77d9b45cb4855f completed March 1, 2026, 10:34 p.m.
Created at: March 1, 2026, 7:59 p.m.