Triple

T21384590
Position Surface form Disambiguated ID Type / Status
Subject Éléonore de Roye E527456 entity
Predicate religiousConflictSide P375 FINISHED
Object Protestant side 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: Protestant side | Statement: [Éléonore de Roye, religiousConflictSide, Protestant side]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: religiousConflictSide
Context triple: [Éléonore de Roye, religiousConflictSide, Protestant side]
  • A. conflictSide chosen
    Indicates that an entity participates as a distinct party or faction on one side of a conflict or dispute.
  • B. religiousConflictBetween
    Indicates a relationship where two entities are in opposition or dispute due to differing religious beliefs, practices, or affiliations.
  • C. hasReligionOfBelligerents
    Indicates that the belligerent parties in a conflict are associated with a particular religion or religious affiliation.
  • D. religiousConflictPeriod
    Indicates a period of time during which conflicts or hostilities occur that are primarily motivated or structured by religious differences or tensions.
  • E. politicalConflict
    Indicates a relationship where entities are engaged in opposing political positions, struggles, or disputes, often involving competition for power, influence, or policy outcomes.
  • 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0f211c08190b3a129eaa725422e completed April 22, 2026, 11:28 a.m.
PD Predicate disambiguation batch_69e6162bbfc88190a3e75859941b2638 completed April 20, 2026, 12:03 p.m.
Created at: April 16, 2026, 5:12 p.m.