Triple

T6669833
Position Surface form Disambiguated ID Type / Status
Subject Polish local government reforms of 1998 E151696 entity
Predicate affectedPolicyAreas P60745 FINISHED
Object education administration 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: education administration | Statement: [Polish local government reforms of 1998, affectedPolicyAreas, education administration]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: affectedPolicyAreas
Context triple: [Polish local government reforms of 1998, affectedPolicyAreas, education administration]
  • A. influencedPolicyArea
    Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
  • B. commonPolicyArea
    Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
  • C. policyAreaScope chosen
    Indicates the specific policy domain or thematic area to which an action, decision, or measure is relevant or applies.
  • D. coversPolicyArea
    Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
  • E. supportsPolicyArea
    Indicates that one entity endorses, advocates for, or is in favor of a particular policy area or domain of public policy.
  • 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_69c687f71fc081909dbd45d6377f6045 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ce738fe88190a5557900efeec7ec completed March 27, 2026, 6:37 p.m.
PD Predicate disambiguation batch_69c6ad09974c81908784300ae218961f completed March 27, 2026, 4:15 p.m.
Created at: March 27, 2026, 2:02 p.m.