Triple
T522457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liverpool Lime Street |
E10846
|
entity |
| Predicate | hasPassengerRole |
P15253
|
FINISHED |
| Object | major regional hub |
—
|
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: major regional hub | Statement: [Liverpool Lime Street, hasPassengerRole, major regional hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerRole Context triple: [Liverpool Lime Street, hasPassengerRole, major regional hub]
-
A.
hasPassengerUsageCategory
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
B.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
C.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
D.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
E.
formerPassengerService
Indicates that an entity previously provided passenger transportation services but no longer does so.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b372408190b3918fec45444674 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f018129c81909494450fcba71b59 |
completed | Feb. 28, 2026, 1:39 p.m. |
| PDg | Predicate description generation | batch_69a2f0f73af88190bc8f00c2047cc8b8 |
completed | Feb. 28, 2026, 1:43 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.