Triple
T4477408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basingstoke railway station |
E100041
|
entity |
| Predicate | hasInformationScreens |
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: [Basingstoke railway station, hasInformationScreens, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInformationScreens Context triple: [Basingstoke railway station, hasInformationScreens, yes]
-
A.
hasCustomerInformationScreens
chosen
Indicates that an entity is equipped with screens or displays that present information specifically intended for customers.
-
B.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
C.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
D.
hasInformationService
Indicates that one entity provides, operates, or is associated with an information-related service for another entity.
-
E.
displays
Indicates that one entity visually presents or shows another entity’s content or information.
- 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_69b34553cbe48190afa8ac1cac285b86 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35728ed508190ba0e882fa62d8848 |
completed | March 13, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69b3563d63008190816e37027e761375 |
completed | March 13, 2026, 12:11 a.m. |
Created at: March 12, 2026, 11:35 p.m.