Triple

T6958129
Position Surface form Disambiguated ID Type / Status
Subject SGI E161298 entity
Predicate founder P104 FINISHED
Object Abbey Silverstone E161298 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: Abbey Silverstone | Statement: [SGI, founder, Abbey Silverstone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abbey Silverstone
Context triple: [SGI, founder, Abbey Silverstone]
  • A. Abbey Silverstone chosen
    Abbey Silverstone is an entrepreneur best known as the founder of the technology company SGI.
  • B. Tessa Quayle
    Tessa Quayle is a passionate human-rights activist whose mysterious death in Kenya drives the political and emotional intrigue at the heart of John le Carré’s novel "The Constant Gardener."
  • C. Diana Sambrooke
    Diana Sambrooke was an English heiress of the early 18th century who became the wife of the prominent military and political figure Lord George Sackville (later Lord George Germain).
  • D. Sarah Aubrey
    Sarah Aubrey is an American television and film producer known for her work on major studio projects and for holding senior executive roles at networks such as TNT and HBO Max.
  • E. Rebecca Yeldham
    Rebecca Yeldham is a film producer known for her work on acclaimed independent and international films, including the adaptation of "The Kite Runner."
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dad240ac8190808014a5b4920b41 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7618df8648190bec6c0aaca312efd completed March 28, 2026, 5:05 a.m.
Created at: March 27, 2026, 2:29 p.m.