Triple

T24322587
Position Surface form Disambiguated ID Type / Status
Subject Russia and Prussia E613008 entity
Predicate hadRivalryAndCooperation P114697 FINISHED
Object mutual relations in Central and Eastern Europe 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: mutual relations in Central and Eastern Europe | Statement: [Russia and Prussia, hadRivalryAndCooperation, mutual relations in Central and Eastern Europe]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hadRivalryAndCooperation
Context triple: [Russia and Prussia, hadRivalryAndCooperation, mutual relations in Central and Eastern Europe]
  • A. allianceOrRivalry chosen
    Indicates a relationship where entities are either cooperating as allies or competing as rivals, capturing both partnership and opposition dynamics.
  • B. hadPrimaryRivalry
    Indicates that one entity was the main or most significant rival of another entity.
  • C. involvesRivalryBetween
    Indicates a relationship in which two or more entities are engaged in rivalry or competitive opposition with one another.
  • D. conflictOrCooperationWith
    Indicates the presence, nature, or degree of either conflict or cooperation between two entities.
  • E. rivalryBasis
    Indicates the underlying reason, cause, or grounds on which a rivalry between entities is based.
  • 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_69e2d7da491c8190b6e6218af50923db completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292ad4cc881908794b501cf70b7a1 completed April 29, 2026, 11:22 p.m.
PD Predicate disambiguation batch_69f1c45f45888190a9ccc225906c34bd completed April 29, 2026, 8:42 a.m.
Created at: April 18, 2026, 1:52 a.m.