Triple
T20356301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Boncassen |
E496655
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Boncassen |
—
|
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: Boncassen | Statement: [Mrs. Boncassen, familyName, Boncassen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boncassen Context triple: [Mrs. Boncassen, familyName, Boncassen]
-
A.
Boncassen
chosen
Boncassen is the surname of an American academic family featured in Anthony Trollope’s novel "The Duke’s Children."
-
B.
Balzar
Balzar is a town and agricultural center in coastal Ecuador, known for its rice and banana production within Guayas Province.
-
C.
Berlaar
Berlaar is a municipality in the Belgian province of Antwerp, known for its rural character and location along the Nete River.
-
D.
Bonatchiesse
Bonatchiesse is a small alpine village in the Swiss canton of Valais, known for its scenic mountain surroundings and outdoor recreation opportunities.
-
E.
Rodemack
Rodemack is a historic fortified village in northeastern France, renowned for its well-preserved medieval ramparts and picturesque old town.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67853f10881908ecde94036804a8a |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:25 a.m.