Triple
T1177429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humboldt Bay |
E25059
|
entity |
| Predicate | hasInlet |
P23365
|
FINISHED |
| Object | North Bay |
E137371
|
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: North Bay | Statement: [Humboldt Bay, hasInlet, North Bay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: North Bay Context triple: [Humboldt Bay, hasInlet, North Bay]
-
A.
North Bay
North Bay is a small city in northeastern Ontario, Canada, located on the shore of Lake Nipissing and known as a regional transportation and service hub.
-
B.
North Bay
North Bay is a subregion of the San Francisco Bay Area known for its scenic landscapes, wine country, and coastal communities north of the Golden Gate Bridge.
-
C.
North Bay
chosen
North Bay is the northern section of Biscayne Bay in South Florida, known for its coastal neighborhoods, waterways, and proximity to the Miami metropolitan area.
-
D.
Caledon
Caledon is a largely rural town in southern Ontario, Canada, known for its scenic landscapes and inclusion within the Greater Toronto Area.
-
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 (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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd0ebbd08190a441d16a5b65a15e |
completed | March 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4680a04481909e828a70d7fb24ed |
completed | March 8, 2026, 9:50 a.m. |
Created at: March 1, 2026, 7:45 p.m.