Triple
T15853746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stranraer Harbour |
E384402
|
entity |
| Predicate | servedPassengerTraffic |
P120781
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Stranraer Harbour, servedPassengerTraffic, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedPassengerTraffic Context triple: [Stranraer Harbour, servedPassengerTraffic, yes]
-
A.
passengerTraffic
Indicates the flow or volume of passengers moving through or using a particular transport service, route, or facility.
-
B.
servesPassengerTrafficType
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
C.
hasAnnualPassengerTrafficOver
Indicates that the subject location or transport facility experiences an annual passenger volume exceeding a specified threshold.
-
D.
hasPassengerTrafficFrom
Indicates that an entity receives or handles passenger traffic originating from another entity.
-
E.
servesPassengerTrafficTo
Indicates that a transportation facility or service provides regular passenger traffic access or operations to a particular location or area.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:50 a.m.