Triple
T759788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyne Burn gorge |
E16040
|
entity |
| Predicate | proximityToCityCentre |
P1299
|
FINISHED |
| Object | near Dunfermline town centre |
—
|
LITERAL 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: near Dunfermline town centre | Statement: [Lyne Burn gorge, proximityToCityCentre, near Dunfermline town centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToCityCentre Context triple: [Lyne Burn gorge, proximityToCityCentre, near Dunfermline town centre]
-
A.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
B.
isInCountySeatProximity
Indicates that one location lies within a defined close distance to the county seat of a given county.
-
C.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
-
D.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
E.
passesNearCity
Indicates that the path, route, or trajectory of one entity goes close to, but not necessarily through, a specified city.
- F. None of above.
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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a68158508190998da10e69252662 |
completed | March 1, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69a4a5048a8081908d0542214142664a |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.