Triple
T18363886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mattole Beach |
E439988
|
entity |
| Predicate | nearestTown |
P350
|
FINISHED |
| Object | Petrolia |
—
|
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: Petrolia | Statement: [Mattole Beach, nearestTown, Petrolia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Petrolia Context triple: [Mattole Beach, nearestTown, Petrolia]
-
A.
Petrolia
chosen
Petrolia is a small, remote community in Northern California known as a gateway to the rugged, sparsely populated Lost Coast region.
-
B.
Petrolia, Ontario
Petrolia, Ontario is a small Canadian town historically known as the birthplace of the country’s oil industry, located in the Lambton County region of Southwestern Ontario.
-
C.
Wallaceburg
Wallaceburg is a small community in southwestern Ontario, Canada, known historically for its glass, sugar, and manufacturing industries along the Sydenham River.
-
D.
Eganville
Eganville is a small community in eastern Ontario, Canada, known for its location along the Bonnechere River and nearby limestone caves.
-
E.
Fort Frances
Fort Frances is a small Canadian town in northwestern Ontario located on the Rainy River along the U.S. border opposite International Falls, Minnesota.
- 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e516de778c8190a75335ced4e1f834 |
completed | April 19, 2026, 5:54 p.m. |
Created at: April 10, 2026, 10:37 a.m.