Triple
T12624277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darcey Bussell |
E301469
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Darcey |
E514959
|
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: Darcey | Statement: [Darcey Bussell, givenName, Darcey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darcey Context triple: [Darcey Bussell, givenName, Darcey]
-
A.
Dayna
Dayna is a given name, typically used as a feminine variant of the name Dana.
-
B.
Darcie
chosen
Darcie is a given name commonly used as a feminine first name in English-speaking countries.
-
C.
Kayely
Kayely is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
-
D.
Dorraine
Dorraine is an alternate given name of Vivian Liberto, best known as the first wife of country music legend Johnny Cash.
-
E.
Pearce
Pearce is a surname and given name of English origin, commonly considered a variant of "Pierce" and ultimately derived from the name "Peter."
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9610a897c8190a96f3c78d4b270a2 |
completed | April 10, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ed8d81c8190baed4292ce3a74a1 |
completed | May 2, 2026, 8:30 p.m. |
Created at: April 9, 2026, 5:14 p.m.