Triple
T10411318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skarloey Railway |
E245396
|
entity |
| Predicate | hasPrimaryTraffic |
P59443
|
FINISHED |
| Object | passengers |
—
|
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: passengers | Statement: [Skarloey Railway, hasPrimaryTraffic, passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryTraffic Context triple: [Skarloey Railway, hasPrimaryTraffic, passengers]
-
A.
hasPrimaryTrafficType
chosen
Indicates that an entity is associated with a main or predominant type of traffic it handles or is designed for.
-
B.
hasTrafficFeature
Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
-
C.
hasTrafficFunction
Indicates that an entity performs, supports, or is assigned a specific function or role related to traffic management or control.
-
D.
hasPrimary
Indicates that one entity is designated as the main or most important instance (the primary) in relation to another entity.
-
E.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9fc72d081908d81c71133973daf |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb6f160819090040644a12395ec |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:09 p.m.