Triple

T13325212
Position Surface form Disambiguated ID Type / Status
Subject Francis Grose E317422 entity
Predicate name P16 FINISHED
Object Francis Grose E317422 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: Francis Grose | Statement: [Francis Grose, name, Francis Grose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Francis Grose
Context triple: [Francis Grose, name, Francis Grose]
  • A. Francis Grose chosen
    Francis Grose was an 18th-century British antiquary, draughtsman, and author best known for his illustrated works on ancient monuments and his influential slang dictionary.
  • B. Philip Wilson Steer
    Philip Wilson Steer was a leading British Impressionist painter and influential art teacher of the late 19th and early 20th centuries.
  • C. Francis Jeffrey
    Francis Jeffrey was a prominent Scottish judge, literary critic, and editor of the influential Edinburgh Review in the early 19th century.
  • D. George Aislabie
    George Aislabie was an 18th-century English figure known primarily as the son of prominent politician and Chancellor of the Exchequer John Aislabie.
  • E. Charles Hamilton Smith
    Charles Hamilton Smith was a 19th-century British soldier, naturalist, illustrator, and zoologist known for his detailed studies and depictions of animals.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9992c1fec8190bcb6a6bb3c973a24 completed April 11, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7266cfb3c8190ac9ccb7696d02922 completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 9:30 p.m.