Triple

T28721230
Position Surface form Disambiguated ID Type / Status
Subject 2010–2011 Belgian government formation crisis E730098 entity
Predicate policyAreaAffected P148602 FINISHED
Object budgetary policy 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: budgetary policy | Statement: [2010–2011 Belgian government formation crisis, policyAreaAffected, budgetary policy]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: policyAreaAffected
Context triple: [2010–2011 Belgian government formation crisis, policyAreaAffected, budgetary policy]
  • A. policyAreaScope
    Indicates the specific policy domain or thematic area to which an action, decision, or measure is relevant or applies.
  • B. influencedPolicyArea
    Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
  • C. commonPolicyArea
    Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
  • D. policyFocus
    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.
  • E. policyTopic chosen
    Indicates that one entity is about, concerned with, or categorized under a particular policy-related subject or theme.
  • 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_69f043e91fe48190b73bcd8e08d433e0 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f6a28c7c148190bfc980aad9f678ca completed May 3, 2026, 1:19 a.m.
PD Predicate disambiguation batch_69f69fe1e3c88190830bb2e9f407357e completed May 3, 2026, 1:07 a.m.
Created at: April 28, 2026, 5:53 a.m.