Triple

T7780955
Position Surface form Disambiguated ID Type / Status
Subject Oscar Folsom E221514 entity
Predicate spouse P13 FINISHED
Object Emma Harmon Folsom E241045 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: Emma Harmon Folsom | Statement: [Oscar Folsom, spouse, Emma Harmon Folsom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emma Harmon Folsom
Context triple: [Oscar Folsom, spouse, Emma Harmon Folsom]
  • A. Emma Harmon Folsom chosen
    Emma Harmon Folsom was the mother of Frances Folsom Cleveland, who became First Lady of the United States as the wife of President Grover Cleveland.
  • B. Elizabeth Griscom
    Elizabeth Griscom, better known as Betsy Ross, was an American upholsterer and seamstress traditionally credited with sewing the first flag of the United States.
  • C. Elizabeth Wendell
    Elizabeth Wendell was a colonial-era New England woman best known as the mother of Dorothy Quincy, who became the wife of American Founding Father John Hancock.
  • D. Florence Johnston
    Florence Johnston is the sharp-tongued, quick-witted housekeeper on the classic American sitcom "The Jeffersons."
  • E. Emma Gillett
    Emma Gillett was an American lawyer and pioneering advocate for women's legal education who co-founded what became the Washington College of Law.
  • 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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69caa4d6cf9881909f5220437db13cc7 completed March 30, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf5c1f20c81908ae2fc35550b91b5 completed March 30, 2026, 10:14 p.m.
Created at: March 30, 2026, 4:20 p.m.