Triple

T994090
Position Surface form Disambiguated ID Type / Status
Subject Mr. Secretary E21455 entity
Predicate titlePositionRelation P21675 FINISHED
Object used when directly addressing the officeholder 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: used when directly addressing the officeholder | Statement: [Mr. Secretary, titlePositionRelation, used when directly addressing the officeholder]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: titlePositionRelation
Context triple: [Mr. Secretary, titlePositionRelation, used when directly addressing the officeholder]
  • A. stylePositioning
    Indicates how an entity is spatially or visually arranged or aligned relative to a reference frame or other elements.
  • B. namePosition
    Indicates the positional or ordering relationship of a name within a sequence or structured context (e.g., first, last, or specific index).
  • C. subjectPosition
    Indicates the spatial or logical position of a subject relative to a reference frame, context, or other entities.
  • D. positioning
    Indicates the spatial or contextual arrangement of one entity relative to another or within a given environment.
  • E. positionedAgainst
    Indicates that one entity is placed so that it directly faces or is set opposite to another entity, often in close or contacting alignment.
  • F. None of above. chosen

Provenance (4 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4c5e16881908cd5f7ba2fcd5084 completed March 1, 2026, 9:51 p.m.
PD Predicate disambiguation batch_69a4b2af071c819086c374a16307dfe0 completed March 1, 2026, 9:42 p.m.
PDg Predicate description generation batch_69a4b30efd2c8190b780a6dee086d0aa completed March 1, 2026, 9:43 p.m.
Created at: March 1, 2026, 7:41 p.m.