Triple

T865396
Position Surface form Disambiguated ID Type / Status
Subject Second Baldwin government E18689 entity
Predicate domesticPolicyArea P1876 FINISHED
Object industrial relations 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: industrial relations | Statement: [Second Baldwin government, domesticPolicyArea, industrial relations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: domesticPolicyArea
Context triple: [Second Baldwin government, domesticPolicyArea, industrial relations]
  • A. commonPolicyArea
    Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
  • B. 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.
  • C. mainPoliticalDevelopment
    Indicates the primary or most significant political change, event, or evolution affecting an entity within a given period or context.
  • D. politicalSphere
    Indicates involvement or relevance within the domain of politics, governance, or public policy activities and interactions.
  • E. demographicPolicy
    Indicates a relationship where an authority or organization establishes or applies rules and measures intended to influence the size, structure, or composition of a population.
  • 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_69a4938ce8688190a24bdfef82ba7d21 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac6acc148190bcc00a1e939ace77 completed March 1, 2026, 9:15 p.m.
PD Predicate disambiguation batch_69a4aa86065881909d477e26fdd84d45 completed March 1, 2026, 9:07 p.m.
Created at: March 1, 2026, 7:39 p.m.