Triple

T8534573
Position Surface form Disambiguated ID Type / Status
Subject John Marshall E202045 entity
Predicate spouse P13 FINISHED
Object Mary Willis Ambler E202045 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 Willis Ambler | Statement: [John Marshall, spouse, Mary Willis Ambler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Willis Ambler
Context triple: [John Marshall, spouse, Mary Willis Ambler]
  • A. Mary Willis Ambler chosen
    Mary Willis Ambler was the wife of U.S. Supreme Court Chief Justice John Marshall and a member of a prominent Virginia family in the late 18th and early 19th centuries.
  • B. Ethel Fogg Anderson
    Ethel Fogg Anderson was the mother of acclaimed American actor Montgomery Clift.
  • C. Mary Bingham
    Mary Bingham is a notable member of the prominent Bingham family, recognized for her association with this influential lineage.
  • D. Mary Evelyn Tucker
    Mary Evelyn Tucker is a scholar of religion and ecology, co-founder of Yale’s Forum on Religion and Ecology, known for her work integrating environmental ethics with religious and philosophical thought.
  • E. Virginia Kellogg
    Virginia Kellogg was an American screenwriter best known for her hard-hitting crime and prison dramas in mid-20th-century Hollywood.
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6a0ccd4819097b41d0dfb1c5018 completed March 31, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce890eb0b48190aa76cc955d00ec18 completed April 2, 2026, 3:19 p.m.
Created at: March 30, 2026, 6:17 p.m.