Triple

T1270875
Position Surface form Disambiguated ID Type / Status
Subject Rutte III cabinet E15704 entity
Predicate socialPolicyFocus P1876 FINISHED
Object labor market reform 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: labor market reform | Statement: [Rutte III cabinet, socialPolicyFocus, labor market reform]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: socialPolicyFocus
Context triple: [Rutte III cabinet, socialPolicyFocus, labor market reform]
  • A. policyFocus chosen
    Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
  • B. commonPolicyArea
    Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
  • C. issuesPolicyOn
    Indicates that an authority or organization formally creates, approves, or enacts a policy concerning a particular subject or domain.
  • D. socialIssue
    Indicates a relationship where something is recognized or treated as a problem or concern affecting society or a community at large.
  • E. policyStance
    Indicates the position or viewpoint an entity holds regarding a specific policy or set of policies.
  • 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.