Triple
T14939723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caney River |
E372489
|
entity |
| Predicate | hasCityOnRiver |
P17819
|
FINISHED |
| Object | Ramona, Oklahoma |
—
|
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: Ramona, Oklahoma | Statement: [Caney River, hasCityOnRiver, Ramona, Oklahoma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramona, Oklahoma Context triple: [Caney River, hasCityOnRiver, Ramona, Oklahoma]
-
A.
Ramona, Oklahoma
chosen
Ramona, Oklahoma is a small rural town in northeastern Oklahoma known for its quiet community and location within Washington County.
-
B.
Ramona, Kansas
Ramona, Kansas is a small rural city located in central Kansas within Marion County.
-
C.
Ketchum, Oklahoma
Ketchum, Oklahoma is a small town in northeastern Oklahoma known for its proximity to Grand Lake O’ the Cherokees and its rural community character.
-
D.
Tuttle, Oklahoma
Tuttle, Oklahoma is a small city in central Oklahoma known for its agricultural roots and proximity to the Oklahoma City metropolitan area.
-
E.
Blanchard, Oklahoma
Blanchard, Oklahoma is a small city in central Oklahoma that serves as a bedroom community within the Oklahoma City metropolitan area.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64a2f24819099b21566756668a2 |
completed | April 15, 2026, 12:05 a.m. |
Created at: April 10, 2026, 2:38 a.m.