Triple
T29069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunfermline Town railway station |
E579
|
entity |
| Predicate | hasServicePattern |
P849
|
FINISHED |
| Object | local stopping services |
—
|
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: local stopping services | Statement: [Dunfermline Town railway station, hasServicePattern, local stopping services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServicePattern Context triple: [Dunfermline Town railway station, hasServicePattern, local stopping services]
-
A.
hasServiceType
chosen
Indicates that an entity is associated with or categorized by a particular type of service.
-
B.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular service.
-
C.
hasUserService
Indicates that an entity is associated with or utilizes a particular user-related service.
-
D.
hasCharacteristic
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
E.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486d40348190b2d21fc444f499a6 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.