Triple
T20595920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonnells Bay |
E506048
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Morisset |
—
|
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: Morisset | Statement: [Bonnells Bay, locatedNear, Morisset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morisset Context triple: [Bonnells Bay, locatedNear, Morisset]
-
A.
Morisset
chosen
Morisset is a town in the City of Lake Macquarie, New South Wales, Australia, known as a regional centre near the southern end of Lake Macquarie.
-
B.
Montignez
Montignez is a small former municipality in the canton of Jura in northwestern Switzerland, near the French border.
-
C.
Chanteheux
Chanteheux is a commune in the Meurthe-et-Moselle department in northeastern France.
-
D.
Maincy
Maincy is a commune in north-central France best known for encompassing the Château and Gardens of Vaux-le-Vicomte.
-
E.
Duchesne
Duchesne refers to Antoine Nicolas Duchesne, an 18th-century French botanist and horticulturist known for his pioneering work on strawberries and other cultivated plants.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1bea1c81908b85f38b2a471285 |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:40 a.m.