Triple

T203190
Position Surface form Disambiguated ID Type / Status
Subject Madam Speaker E4551 entity
Predicate contrastsWith P278 FINISHED
Object Mister Speaker E3628 NE 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: Mister Speaker | Statement: [Madam Speaker, contrastsWith, Mister Speaker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mister Speaker
Context triple: [Madam Speaker, contrastsWith, Mister Speaker]
  • A. Mister Speaker chosen
    Mister Speaker is the traditional formal address used for a male Speaker presiding over the United States House of Representatives.
  • B. The Politician
    The Politician is a 17th-century stage play by English dramatist James Shirley, known as one of his notable tragic works exploring court intrigue and moral corruption.
  • C. Madam Speaker
    "Madam Speaker" is the formal mode of address used for a woman serving as Speaker of the United States House of Representatives.
  • D. Mr. Secretary
    Mr. Secretary is the formal style of address traditionally used for the United States Secretary of Defense.
  • E. Mr. Secretary
    "Mr. Secretary" is the traditional formal style of address used for the United States Secretary of the Treasury.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a25737567c81908f9c505300239181 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25be7337481909f4937fc1a06fb53 completed Feb. 28, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69a32813ed0c8190bebd5129eb5ebfe7 completed Feb. 28, 2026, 5:38 p.m.
Created at: Feb. 28, 2026, 2:51 a.m.