Triple
T22047459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berwick-upon-Tweed railway station |
E544797
|
entity |
| Predicate | hasDigitalInformationScreens |
P3794
|
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: [Berwick-upon-Tweed railway station, hasDigitalInformationScreens, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDigitalInformationScreens Context triple: [Berwick-upon-Tweed railway station, hasDigitalInformationScreens, yes]
-
A.
hasDigitalSystem
Indicates that an entity possesses, uses, or is equipped with a digital system (such as software, hardware, or an integrated digital platform).
-
B.
hasCustomerInformationScreens
chosen
Indicates that an entity is equipped with screens or displays that present information specifically intended for customers.
-
C.
hasDigitalAccess
Indicates that an entity has the ability or permission to use or access digital resources, services, or information.
-
D.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
E.
hasPhysicalDisplays
Indicates that an entity possesses one or more tangible, visible display units or interfaces.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12830c674819080254d77ee02bc9f |
completed | April 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:26 p.m.