Triple
T21118925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorking Deepdene railway station |
E520372
|
entity |
| Predicate | isSmallStop |
P142922
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dorking Deepdene railway station, isSmallStop, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSmallStop Context triple: [Dorking Deepdene railway station, isSmallStop, true]
-
A.
isSmall
Indicates that one entity has a size that is relatively small, either in absolute terms or compared to a reference standard or another entity.
-
B.
isSmallCity
Indicates that a city has a relatively small population size or limited geographic/urban extent compared to typical cities.
-
C.
isSmallForce
Indicates that the force involved has a relatively low magnitude compared to typical or relevant reference forces.
-
D.
isSmallScale
Indicates that the related activity, operation, or entity occurs on a limited or minor scale, involving relatively small size, scope, or capacity.
-
E.
isSmallestOf
Indicates that an entity has the minimum size or value within a specified set or group of entities.
- F. None of above. chosen
Provenance (4 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7223176c48190bfbaea41c2209a15 |
completed | April 21, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:55 p.m.