Triple

T2632403
Position Surface form Disambiguated ID Type / Status
Subject Spartacist uprising E59663 entity
Predicate hasTypeOfConflict P1397 FINISHED
Object civil 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: civil conflict | Statement: [Spartacist uprising, hasTypeOfConflict, civil conflict]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTypeOfConflict
Context triple: [Spartacist uprising, hasTypeOfConflict, civil conflict]
  • A. hasConflictStatus
    Indicates that there exists a state of conflict or dispute associated with the relationship between the involved entities.
  • B. hasOngoingConflict
    Indicates that there is a current, unresolved state of opposition, dispute, or hostilities between the related entities.
  • C. conflictType chosen
    Indicates the specific kind or category of conflict that characterizes the relationship or interaction between entities.
  • D. appliesToConflictWith
    Indicates that one element’s scope, rules, or effects are relevant to a conflict involving another element, defining how that element is implicated in or governed by the conflict.
  • E. conflictWith
    Indicates that two entities are in opposition or disagreement, such that their goals, actions, or states are incompatible or interfere with each other.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abdb0e7b888190bfa5d2e33f00ec0f completed March 7, 2026, 8 a.m.
PD Predicate disambiguation batch_69abd810d7f481908e81c305772c4c14 completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:50 p.m.