Triple
T21142116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kirk Fell |
E520957
|
entity |
| Predicate | nearMountain |
P31783
|
FINISHED |
| Object | Grey Knotts |
—
|
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: Grey Knotts | Statement: [Kirk Fell, nearMountain, Grey Knotts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grey Knotts Context triple: [Kirk Fell, nearMountain, Grey Knotts]
-
A.
Grey Knotts
chosen
Grey Knotts is a fell in England’s Lake District, known for its rugged terrain and panoramic views over the surrounding valleys and passes.
-
B.
Shipman Knotts
Shipman Knotts is a small fell in England’s Lake District, known for its rocky outcrops and views over the Kentmere valley.
-
C.
Marcus Hooks
Marcus Hooks is a legendary, influential figure in Louis Hinds' world, revered enough to be honored with a tribute.
-
D.
Burford Tolsey
Burford Tolsey is a historic former market and meeting hall in Burford, Oxfordshire, now serving as a museum showcasing the town’s local history.
-
E.
Eppa Hunton
Eppa Hunton was a Confederate brigadier general in the American Civil War who later became a U.S. Congressman and Senator from Virginia.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e723f96cf081909d10309e08aeca93 |
completed | April 21, 2026, 7:15 a.m. |
Created at: April 16, 2026, 2:57 p.m.