Triple

T2697567
Position Surface form Disambiguated ID Type / Status
Subject Mr. Secretary E58547 entity
Predicate isCounterpartOf P6587 FINISHED
Object Madam Secretary E21919 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: Madam Secretary | Statement: [Mr. Secretary, isCounterpartOf, Madam Secretary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madam Secretary
Context triple: [Mr. Secretary, isCounterpartOf, Madam Secretary]
  • A. Madam Secretary
    "Madam Secretary" is the formal honorific used to address a woman serving in a high-ranking government secretary position, such as the Secretary of the Treasury.
  • B. Madam Secretary chosen
    Madam Secretary is the formal honorific used to address a woman serving as a cabinet-level secretary in the United States government.
  • C. Madam Secretary
    "Madam Secretary" is the formal honorific style used to address a female Secretary of State in California.
  • D. Madam Secretary
    "Madam Secretary" is the formal style of address used when speaking to or about a female United States Secretary of the Army.
  • E. Madam Secretary
    "Madam Secretary" is the formal honorific used to address a woman serving as the United States Secretary of State.
  • 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_69ab4ac269e481909cb317d79e68b75b completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda322af48190833b8a3c006db236 completed March 7, 2026, 7:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf6d9d9c81908c7c1bcdfb7810f0 completed March 10, 2026, 5:43 a.m.
Created at: March 6, 2026, 9:55 p.m.