Triple

T26473005
Position Surface form Disambiguated ID Type / Status
Subject Speaker pro tempore E665949 entity
Predicate mayHaveVariantTitle P110696 FINISHED
Object Speaker pro tem NE NERFINISHED

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: Speaker pro tem | Statement: [Speaker pro tempore, mayHaveVariantTitle, Speaker pro tem]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mayHaveVariantTitle
Context triple: [Speaker pro tempore, mayHaveVariantTitle, Speaker pro tem]
  • A. titleVariesBy
    Indicates that the title associated with an entity changes depending on context, conditions, or another varying attribute.
  • B. hasWorkTitleVariant
    Indicates that an entity has an alternative or variant form of its work title, such as a different wording, spelling, or language version of the same title.
  • C. haveAlternativeTitle chosen
    Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
  • D. titleVariant
    Indicates that one title is an alternative or variant form of another title referring to the same work or entity.
  • E. hasVariantsIn
    Indicates that an entity exists in multiple alternative forms or versions within a specified context or set.
  • 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_69ee883f80dc819090e311b022b78e02 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f61a17a7788190946f7e32d63cd43f completed May 2, 2026, 3:36 p.m.
PD Predicate disambiguation batch_69f611ab768c8190b1849c15a3e59dda completed May 2, 2026, 3 p.m.
Created at: April 27, 2026, 12:21 a.m.