Triple

T136223
Position Surface form Disambiguated ID Type / Status
Subject Mary Barra E2752 entity
Predicate birthName P65 FINISHED
Object Mary Teresa 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 Teresa Barra | Statement: [Mary Barra, birthName, Mary Teresa Barra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Teresa Barra
Context triple: [Mary Barra, birthName, Mary Teresa 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. 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.
  • D. Alan Mulally
    Alan Mulally is an American engineer and business executive best known for leading Ford Motor Company’s turnaround as its CEO during the late 2000s financial crisis.
  • E. Augusta Dearborn
    Augusta Dearborn was the woman in whose honor the city of Augusta, Maine, received its name.
  • 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a257a4edf081908c494c8370c76b9a completed Feb. 28, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2b4bad1a0819098459e2a9d6b8d2a completed Feb. 28, 2026, 9:26 a.m.
Created at: Feb. 28, 2026, 2:30 a.m.