Triple
T18287710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Beazley |
E438025
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Beazley |
—
|
NE NERFINISHED |
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: Beazley | Statement: [Samuel Beazley, familyName, Beazley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beazley Context triple: [Samuel Beazley, familyName, Beazley]
-
A.
Beazley
chosen
Beazley is an English-language surname most prominently associated with Australian politician Kim Beazley and his family.
-
B.
Beazley Group
Beazley Group is a specialist insurance company headquartered in London, known for underwriting a wide range of commercial insurance and reinsurance risks worldwide.
-
C.
Ashbee
Ashbee is an English surname most notably associated with C. R. Ashbee, a prominent designer and key figure in the Arts and Crafts movement.
-
D.
Beeton
Beeton is the surname most famously associated with Mrs. Isabella Beeton, the 19th-century English author of the influential household management and cookery book "Mrs Beeton's Book of Household Management."
-
E.
Smythson
Smythson is a luxury British stationery and leather goods brand renowned for its high-end notebooks, diaries, and accessories.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500faf62081908f16ebee0a195ba2 |
completed | April 19, 2026, 4:21 p.m. |
Created at: April 10, 2026, 10:35 a.m.