Triple

T15154132
Position Surface form Disambiguated ID Type / Status
Subject Ministry of the Navy of Spain E362025 entity
Predicate hasOfficeHeldBy P67246 FINISHED
Object Minister of the Navy of 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: Minister of the Navy of Spain | Statement: [Ministry of the Navy of Spain, hasOfficeHeldBy, Minister of the Navy of Spain]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOfficeHeldBy
Context triple: [Ministry of the Navy of Spain, hasOfficeHeldBy, Minister of the Navy of Spain]
  • A. hasMemberWhoHeldOffice
    Indicates that a group or organization includes at least one member who has held a specified office or position.
  • B. hasHistoricalOfficeHolder chosen
    Indicates that an office, position, or role has been held by a specific person at some point in the past.
  • C. hasListOfOfficeHolders
    Indicates that an entity is associated with a collection or record enumerating the individuals who have held a particular office or position.
  • D. heldPoliticalOfficeIn
    Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
  • E. hasHeldOfficeType
    Indicates that an entity has at some time occupied or served in a specified type or category of office or position.
  • 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_69d85a0759908190b8a051d2e2a1cbe6 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060b0cd08190afad14cffcc7d93f completed April 15, 2026, 9:41 p.m.
PD Predicate disambiguation batch_69deb9779acc81908ed2dad382c42dca completed April 14, 2026, 10:02 p.m.
Created at: April 10, 2026, 3:08 a.m.