Triple
T9941316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zumbro River |
E194087
|
entity |
| Predicate | hasCityOnRiver |
P17819
|
FINISHED |
| Object | Oronoco, Minnesota |
E618382
|
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: Oronoco, Minnesota | Statement: [Zumbro River, hasCityOnRiver, Oronoco, Minnesota]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oronoco, Minnesota Context triple: [Zumbro River, hasCityOnRiver, Oronoco, Minnesota]
-
A.
Oronoco, Minnesota
chosen
Oronoco, Minnesota is a small city in southeastern Minnesota known for its rural character and proximity to Rochester.
-
B.
Onalaska
Onalaska is a city in western Wisconsin, United States, located along the Mississippi River just north of La Crosse.
-
C.
Eyota, Minnesota
Eyota, Minnesota is a small city in southeastern Minnesota that serves as a rural community near the regional hub of Rochester.
-
D.
Nisswa, Minnesota
Nisswa, Minnesota is a small resort city in central Minnesota known for its lakes, tourism, and outdoor recreation.
-
E.
Oronogo, Missouri
Oronogo, Missouri is a small city in southwestern Missouri that forms part of the Joplin metropolitan area.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb610905c81909d669265c92021a5 |
completed | April 2, 2026, 12:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d229080d0081908b66b9c4166db252 |
completed | April 5, 2026, 9:19 a.m. |
Created at: March 30, 2026, 8:44 p.m.