Triple
T18714527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beverley railway station |
E457599
|
entity |
| Predicate | hasSelfServiceTicketMachine |
P49831
|
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: [Beverley railway station, hasSelfServiceTicketMachine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSelfServiceTicketMachine Context triple: [Beverley railway station, hasSelfServiceTicketMachine, yes]
-
A.
hasSelfServiceTicketMachines
chosen
Indicates that an entity is equipped with self-service ticket machines available for use.
-
B.
hasSecurityTerminal
Indicates that an entity is equipped with or contains a security terminal used for access control, monitoring, or security-related operations.
-
C.
hasVIPTerminal
Indicates that one entity possesses or provides access to a VIP (very important person) terminal associated with another entity.
-
D.
ticketMachines
Indicates that there is a relationship involving ticket machines, typically denoting where they are located, available, or associated with a particular entity or place.
-
E.
hasTerminalFacility
Indicates that an entity possesses or includes a terminal facility used as an endpoint for transport, communication, or related operations.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56ab4ee6881908f19558937cbb078 |
completed | April 19, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69e478e0889c8190a118d67b200ce8ef |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:50 a.m.