Triple

T1270873
Position Surface form Disambiguated ID Type / Status
Subject Rutte III cabinet E15704 entity
Predicate climatePolicyGoal P14666 FINISHED
Object CO2 emissions reduction 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: CO2 emissions reduction | Statement: [Rutte III cabinet, climatePolicyGoal, CO2 emissions reduction]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: climatePolicyGoal
Context triple: [Rutte III cabinet, climatePolicyGoal, CO2 emissions reduction]
  • A. politicalGoal
    Indicates a relationship where an entity aims to achieve, promote, or realize a specific political outcome, policy, or state of affairs.
  • B. ideologicalGoal
    Indicates that an entity aims to promote, realize, or advance a particular ideology or set of ideological principles.
  • C. hasPolicyGoal chosen
    Indicates that an entity is associated with, or aims to achieve, a specific policy objective or target.
  • D. strategicGoal
    Indicates that one entity represents a long-term objective or desired outcome that another entity is intentionally aiming to achieve or align actions toward.
  • E. climateChangeIndicator
    Indicates that the subject serves as a sign, measure, or signal of the presence, extent, or impact of climate change on the related object or context.
  • 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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c06ae7b88190a1e0b5232d84a7b1 completed March 1, 2026, 10:40 p.m.
PD Predicate disambiguation batch_69a4bede52a081909665d60acbe41d31 completed March 1, 2026, 10:34 p.m.
Created at: March 1, 2026, 7:50 p.m.