Triple
T19863055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dale family |
E477316
|
entity |
| Predicate | hasNotableMember |
P304
|
FINISHED |
| Object | Bell Dale |
—
|
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: Bell Dale | Statement: [Dale family, hasNotableMember, Bell Dale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bell Dale Context triple: [Dale family, hasNotableMember, Bell Dale]
-
A.
Bell Dale
chosen
Bell Dale is a fictional character from Anthony Trollope’s Barsetshire novel "The Small House at Allington," known as one of the Dale sisters central to the story’s romantic and social dramas.
-
B.
Yafford
Yafford is a small hamlet on the Isle of Wight in England.
-
C.
Grandstaff
Grandstaff is a surname of English origin borne by various individuals, including Olive Kathryn Grandstaff.
-
D.
Tilghman
Tilghman is a surname most notably associated with Shirley M. Tilghman, a prominent molecular biologist and former president of Princeton University.
-
E.
Tilghman
Tilghman is a masculine given name of English origin that has been borne by various notable American figures, including politicians and military officers.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6589c4c0081908cd51ff75441e7ac |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.