Triple

T780565
Position Surface form Disambiguated ID Type / Status
Subject Princess Anne Stuart E16486 entity
Predicate familyName P18 FINISHED
Object Stuart E21325 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: Stuart | Statement: [Princess Anne Stuart, familyName, Stuart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stuart
Context triple: [Princess Anne Stuart, familyName, Stuart]
  • A. Stuart chosen
    Stuart is the royal dynasty that ruled Scotland and later England and Ireland, most famously associated with monarchs such as James I and Charles I.
  • B. Robert Stuart, Duke of Kintyre
    Robert Stuart, Duke of Kintyre, was a short-lived Scottish prince of the early 17th century, born into the House of Stuart as a younger son of King James VI and I.
  • C. Edward Strong
    Edward Strong was the chancellor of the University of California, Berkeley during the 1960s whose administration became a central focus of student opposition in the Free Speech Movement.
  • D. George
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • E. George
    George is a town in South Africa’s Western Cape province, known as a gateway to the Garden Route and for its scenic mountains and forests.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a751ea3481908a622d5255249883 completed March 1, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7edfae07c8190b104c869302cd486 completed March 4, 2026, 8:31 a.m.
Created at: March 1, 2026, 7:37 p.m.