Triple
T4822678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cupar railway station |
E107744
|
entity |
| Predicate | distanceFromReference |
P3387
|
FINISHED |
| Object | approximately 31 miles north of Edinburgh Waverley |
—
|
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: approximately 31 miles north of Edinburgh Waverley | Statement: [Cupar railway station, distanceFromReference, approximately 31 miles north of Edinburgh Waverley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromReference Context triple: [Cupar railway station, distanceFromReference, approximately 31 miles north of Edinburgh Waverley]
-
A.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another entity.
-
B.
distanceFromTerminus
chosen
Indicates the measured distance of an entity from a defined endpoint or terminus along a route, path, or sequence.
-
C.
distanceCharacteristic
Indicates a relationship where an entity is described or constrained by some property or measure of distance (e.g., range, spacing, or separation).
-
D.
distanceFromReading
Indicates the measured spatial distance between a specified entity and the location of Reading.
-
E.
distance
Indicates the spatial separation or length between two points, objects, or locations.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.