Triple

T3564943
Position Surface form Disambiguated ID Type / Status
Subject Anthony Barra E75423 entity
Predicate spouse P13 FINISHED
Object Mary Barra E2752 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: Mary Barra | Statement: [Anthony Barra, spouse, Mary Barra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Barra
Context triple: [Anthony Barra, spouse, Mary Barra]
  • A. Mary Barra chosen
    Mary Barra is an American business executive who became the first female CEO of a major global automaker when she took the helm of General Motors.
  • B. Jim Farley
    Jim Farley is an American business executive who serves as the president and chief executive officer of Ford Motor Company.
  • C. Kathryn Iacocca
    Kathryn Iacocca is known as one of the daughters of famed American automobile executive Lee Iacocca.
  • D. Ursula Burns
    Ursula Burns is an American business executive best known for serving as CEO of Xerox, becoming the first Black woman to lead a Fortune 500 company.
  • E. William Clay Ford Jr.
    William Clay Ford Jr. is an American businessman and great-grandson of Henry Ford who has served as executive chairman of Ford Motor Company and is known for promoting sustainability and innovation within the company.
  • 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_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0a8f6288190928479f5bea32245 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bba91d08819081a433c9f06a2c2b completed March 13, 2026, 7:24 a.m.
Created at: March 8, 2026, 3:21 p.m.