Triple

T28653504
Position Surface form Disambiguated ID Type / Status
Subject Guinean government (alleged support for LURD) E725263 entity
Predicate allegedImpact P54036 FINISHED
Object prolongation of the Liberian conflict 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: prolongation of the Liberian conflict | Statement: [Guinean government (alleged support for LURD), allegedImpact, prolongation of the Liberian conflict]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: allegedImpact
Context triple: [Guinean government (alleged support for LURD), allegedImpact, prolongation of the Liberian conflict]
  • A. indirectImpactOn chosen
    Indicates that one entity affects another entity’s state, condition, or outcome through one or more intermediate factors rather than through a direct interaction.
  • B. canImpact
    Indicates that one entity has the potential or ability to affect, influence, or cause a change in another entity.
  • C. impactDescription
    Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
  • D. exportImpact
    Indicates the effect or consequences that an entity’s exports have on another entity, system, or context.
  • E. recognizesImpactOn
    Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
  • 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_69f01d84f5f0819087ab5e6143b14ed7 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f6db1f3ec48190a82e7d893d3c76ba completed May 3, 2026, 5:20 a.m.
PD Predicate disambiguation batch_69f6d82adfa481908a5e196d2e18c73f completed May 3, 2026, 5:07 a.m.
Created at: April 28, 2026, 4:53 a.m.