Triple

T15792488
Position Surface form Disambiguated ID Type / Status
Subject Peruvian civil conflict (1980s–1990s) E382892 entity
Predicate governmentStrategy P12442 FINISHED
Object counterinsurgency operations 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: counterinsurgency operations | Statement: [Peruvian civil conflict (1980s–1990s), governmentStrategy, counterinsurgency operations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: governmentStrategy
Context triple: [Peruvian civil conflict (1980s–1990s), governmentStrategy, counterinsurgency operations]
  • A. governmentAction chosen
    Indicates actions, decisions, or interventions carried out by a government or its agencies in relation to other entities.
  • B. governmentOutcome
    Indicates the result, consequence, or effect produced by a government’s decisions, actions, or policies.
  • C. governmentInvolvement
    Indicates that a government participates in, influences, regulates, or otherwise plays a role in the specified activity, process, or entity.
  • D. countryGovernment
    Indicates the type or form of government that exercises authority over a given country.
  • E. coordinatesNationalPoliciesFor
    Indicates that one entity organizes and harmonizes national-level policies or strategies across multiple actors or domains.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4d9623081908496cdfdf86a078a completed April 16, 2026, 10:07 a.m.
PD Predicate disambiguation batch_69e00537bd1c81908d6e832792fd934f completed April 15, 2026, 9:37 p.m.
Created at: April 10, 2026, 4:48 a.m.