Triple

T7535613
Position Surface form Disambiguated ID Type / Status
Subject Michael Gough E178141 entity
Predicate spouse P13 FINISHED
Object Diana Graves E178141 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: Diana Graves | Statement: [Michael Gough, spouse, Diana Graves]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diana Graves
Context triple: [Michael Gough, spouse, Diana Graves]
  • A. Diana Graves chosen
    Diana Graves is known as the wife of English character actor Michael Gough, famed for his role as Alfred in the Batman film series.
  • B. Diana Rivers
    Diana Rivers is a compassionate and intelligent clergyman’s daughter in Charlotte Brontë’s novel "Jane Eyre," who becomes one of Jane’s close cousins and friends.
  • C. Diana Rathbun
    Diana Rathbun is a film producer best known for her work on the epic historical war movie "Troy."
  • D. Diana Drake Wilson
    Diana Drake Wilson is an American co-founder of the Museum of Jurassic Technology, an experimental Los Angeles museum known for its enigmatic blend of fact, fiction, art, and science.
  • E. Ruby Gentry
    Ruby Gentry is a 1952 American melodrama film directed by King Vidor, starring Jennifer Jones as a poor Southern woman whose passionate love and social struggles lead to tragedy.
  • 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_69c69f2acdbc8190b5a8320168c1d0ba completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f84c13208190971096a0b81b0ff2 completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856b687708190a1fe1351be70616b completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:47 p.m.