Triple

T7259552
Position Surface form Disambiguated ID Type / Status
Subject Warren Oates E159612 entity
Predicate spouse P13 FINISHED
Object Vickery Oates E159612 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: Vickery Oates | Statement: [Warren Oates, spouse, Vickery Oates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vickery Oates
Context triple: [Warren Oates, spouse, Vickery Oates]
  • A. Vickery Oates chosen
    Vickery Oates is best known as the wife of American character actor Warren Oates.
  • B. Jean Purdy
    Jean Purdy was a British nurse and embryologist who played a pivotal role in developing in vitro fertilization, helping to create the world’s first “test-tube baby.”
  • C. O’Neil Ford
    O’Neil Ford was a prominent 20th-century American architect known for his modernist designs that integrated regional materials and traditions, particularly in Texas.
  • D. Rachel Owen
    Rachel Owen was a Welsh artist, printmaker, and academic known for her work inspired by Dante’s "Divine Comedy" and for her long-term relationship with Radiohead frontman Thom Yorke.
  • E. Mel Sharples
    Mel Sharples is a gruff but good-hearted diner owner and cook from the sitcom "Alice," known for his no-nonsense attitude and catchphrase, "Stow it!"
  • 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_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac5311c819094fc6880f3152813 completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e5269d1c8190a56624530f9af48b completed March 28, 2026, 2:26 p.m.
Created at: March 27, 2026, 2:57 p.m.