Triple

T7294358
Position Surface form Disambiguated ID Type / Status
Subject Samuel P. Huntington E164479 entity
Predicate spouse P13 FINISHED
Object Nancy Arkelyan Huntington E164479 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: Nancy Arkelyan Huntington | Statement: [Samuel P. Huntington, spouse, Nancy Arkelyan Huntington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nancy Arkelyan Huntington
Context triple: [Samuel P. Huntington, spouse, Nancy Arkelyan Huntington]
  • A. Nancy Arkelyan Huntington chosen
    Nancy Arkelyan Huntington is best known as the wife of influential American political scientist Samuel P. Huntington.
  • B. Nancy Wyman
    Nancy Wyman is an American Democratic politician who served as the 108th lieutenant governor of Connecticut and previously chaired the state’s Democratic Party.
  • C. Nancy Goodman
    Nancy Goodman is an American diplomat, businesswoman, and philanthropist best known for founding the Susan G. Komen Breast Cancer Foundation.
  • D. Nancy Rutchik
    Nancy Rutchik is an individual honored as the namesake of the Nancy Rutchik Red Maple Rill, a notable garden feature.
  • E. Rachel Marron
    Rachel Marron is a famous pop singer and actress who becomes the client and love interest of a former Secret Service agent in the romantic thriller film "The Bodyguard."
  • 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_69c6887a499881909dd23341399c59d8 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6eb8b7cc08190983739bf667057c9 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e543c22c8190acf8dcffd9c59520 completed March 28, 2026, 2:27 p.m.
Created at: March 27, 2026, 3 p.m.