Triple
T9638110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Ouse |
E232986
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Skelton |
E728926
|
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: Skelton | Statement: [River Ouse, flowsThrough, Skelton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skelton Context triple: [River Ouse, flowsThrough, Skelton]
-
A.
Skelton
Skelton is a surname most famously associated with American comedian and entertainer Red Skelton.
-
B.
Skelton-in-Cleveland
chosen
Skelton-in-Cleveland is a village and civil parish in North Yorkshire, England, known historically for its ironstone mining and proximity to the North Sea coast.
-
C.
Saddler
Saddler is a surname and occupational term historically referring to someone who makes, repairs, or sells saddles and other horse-related leather equipment.
-
D.
Shikles
Shikles is a surname associated with the American actor Craig Stevens, best known for his role in the television series "Peter Gunn."
-
E.
Snodgrass
Snodgrass is a surname of English and Scottish origin borne by various notable individuals in sports, politics, and the arts.
- 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_69ca848a5a908190aad251f4137b0c3a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b51b08081908e30744607b28953 |
completed | April 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18243cfdc81908ecdf039c38de478 |
completed | April 4, 2026, 9:27 p.m. |
Created at: March 30, 2026, 8:11 p.m.