Triple

T13764758
Position Surface form Disambiguated ID Type / Status
Subject Kathryn Ann Bailey E330709 entity
Predicate associatedWith P37 FINISHED
Object Kay Bailey Hutchison E43128 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: Kay Bailey Hutchison | Statement: [Kathryn Ann Bailey, associatedWith, Kay Bailey Hutchison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kay Bailey Hutchison
Context triple: [Kathryn Ann Bailey, associatedWith, Kay Bailey Hutchison]
  • A. Kay Bailey Hutchison chosen
    Kay Bailey Hutchison is an American attorney and Republican politician who served as a long-time U.S. Senator from Texas.
  • B. Cynthia Lummis
    Cynthia Lummis is a Republican politician from Wyoming who has served as both a U.S. representative and the state's first female U.S. senator.
  • C. Harriet Hageman
    Harriet Hageman is a Republican politician and attorney from Wyoming who serves as the state's at-large U.S. Representative after defeating Liz Cheney in a high-profile 2022 primary.
  • D. Kim Roth
    Kim Roth is a film producer best known for her work on critically acclaimed dramas such as "Mudbound."
  • E. Mari Blanchard
    Mari Blanchard was an American film and television actress of the 1950s and 1960s, known for her roles in Westerns and adventure films.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de022690ac8190bd5410ecc659a2a7 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b0724ab481908448d71a1bd02253 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 10:10 p.m.