Triple

T1857670
Position Surface form Disambiguated ID Type / Status
Subject United States Minister to Spain E41740 entity
Predicate hasEquivalentOffice P15578 FINISHED
Object British Minister to Spain 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: British Minister to Spain | Statement: [United States Minister to Spain, hasEquivalentOffice, British Minister to Spain]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasEquivalentOffice
Context triple: [United States Minister to Spain, hasEquivalentOffice, British Minister to Spain]
  • A. hasAssociatedOffice
    Indicates that an entity is linked to or connected with a particular office in an official or functional capacity.
  • B. hasColleagueOffice
    Indicates that one entity has an office that is shared with or located near the office of another colleague entity.
  • C. equivalentOffice chosen
    Indicates that two offices are considered functionally or formally the same position, role, or authority, even if they differ in name or jurisdiction.
  • D. hasSupportingOffice
    Indicates that an entity is associated with or served by a particular office that provides support or administrative services to it.
  • E. hasOffice
    Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb231de14819091da3a20ed03c430 completed March 7, 2026, 5:05 a.m.
PD Predicate disambiguation batch_69abafde4598819099d8229128348fd3 completed March 7, 2026, 4:55 a.m.
Created at: March 4, 2026, 7:33 p.m.