Triple

T7299348
Position Surface form Disambiguated ID Type / Status
Subject John Milton E167801 entity
Predicate spouse P13 FINISHED
Object Katherine Woodcock E286456 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: Katherine Woodcock | Statement: [John Milton, spouse, Katherine Woodcock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katherine Woodcock
Context triple: [John Milton, spouse, Katherine Woodcock]
  • A. Katherine Woodcock chosen
    Katherine Woodcock was the second wife of the English poet John Milton, remembered primarily through his sonnet mourning her death shortly after childbirth.
  • B. Katherine McCloskey Wilson
    Katherine McCloskey Wilson was the wife of Malcolm Wilson, the 50th Governor of New York.
  • C. Elizabeth Porter
    Elizabeth Porter was the wife of English writer Samuel Johnson, remembered as his older, widowed partner whose marriage to him significantly influenced his early life and career.
  • D. Mary Catlett
    Mary Catlett was the wife of English Anglican clergyman and hymn writer John Newton, known for her supportive role in his life and ministry.
  • E. Katharine Alexander
    Katharine Alexander was an American stage and film actress active in the early to mid-20th century, known for her character roles in Hollywood dramas.
  • 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_69c6888c820881909fc68f689fe1c251 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6ebad1b4481909e49ccc580007e4b completed March 27, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be10c5b081908210981ce9c45bd9 completed March 29, 2026, 5:52 a.m.
Created at: March 27, 2026, 3:01 p.m.