Triple

T2431131
Position Surface form Disambiguated ID Type / Status
Subject Bob Woodward E52846 entity
Predicate spouse P13 FINISHED
Object Kathleen Middlekauff E52846 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: Kathleen Middlekauff | Statement: [Bob Woodward, spouse, Kathleen Middlekauff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kathleen Middlekauff
Context triple: [Bob Woodward, spouse, Kathleen Middlekauff]
  • A. Kathleen Middlekauff chosen
    Kathleen Middlekauff is an American academic and former spouse of investigative journalist and author Bob Woodward.
  • B. Margaret Pomeranz
    Margaret Pomeranz is an Australian film critic and television presenter best known for co-hosting long-running movie review programs such as "The Movie Show" and "At the Movies."
  • C. Mary Louise Miller
    Mary Louise Miller was an actress who appeared in early American silent cinema, including the 1926 film "Sparrows."
  • D. Stacy Schiff
    Stacy Schiff is a Pulitzer Prize–winning American biographer and essayist known for acclaimed works on figures such as Cleopatra, Vera Nabokov, and the Salem witch trials.
  • E. Eileen Power
    Eileen Power was a prominent British economic historian and medievalist known for her influential work on medieval society, trade, and women's history.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9c767a88190b31cbccdce8e8982 completed March 7, 2026, 6:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf68d6a481909acd43eb31660f0e completed March 9, 2026, 12:39 p.m.
Created at: March 6, 2026, 9:43 p.m.