Triple

T13355455
Position Surface form Disambiguated ID Type / Status
Subject Semple E318679 entity
Predicate hasNotableBearer P458 FINISHED
Object David Semple E440382 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: David Semple | Statement: [Semple, hasNotableBearer, David Semple]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Semple
Context triple: [Semple, hasNotableBearer, David Semple]
  • A. David Semple chosen
    David Semple was a British bacteriologist best known for developing an early anti-rabies vaccine while serving in the Indian Medical Service.
  • B. David Geddes
    David Geddes is a cinematographer known for his work on the horror-comedy film "Tucker & Dale vs. Evil."
  • C. Robert Semple
    Robert Semple was an early California pioneer, printer, and political leader who played a key role in the transition of California to statehood.
  • D. Paul Duguid
    Paul Duguid is a scholar of information studies and co-author of the influential book "The Social Life of Information" with John Seely Brown.
  • E. David Cunningham
    David Cunningham is a relatively common personal name shared by various notable individuals across fields such as sports, academia, and the arts.
  • 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99f1ef94c81909a59b7c3f77d3335 completed April 11, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c6f78e088190a2d241042cfe615f completed May 3, 2026, 10:06 p.m.
Created at: April 9, 2026, 9:32 p.m.