Triple
T17329366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Gosforth Metro station |
E420771
|
entity |
| Predicate | hasNextTrainDisplays |
P53774
|
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: [South Gosforth Metro station, hasNextTrainDisplays, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNextTrainDisplays Context triple: [South Gosforth Metro station, hasNextTrainDisplays, yes]
-
A.
hasNextTrainIndicators
chosen
Indicates that there are one or more indicators providing information about the next train in a sequence or schedule.
-
B.
followingTrainStatus
Indicates that one entity is tracking or monitoring the current operational status or progress of a train.
-
C.
hasRollingStockOnDisplay
Indicates that a location or entity has railway rolling stock (such as locomotives or carriages) exhibited for public viewing.
-
D.
trainsOn
Indicates that one entity receives training, instruction, or practice using or based on another entity (such as a resource, dataset, tool, or subject).
-
E.
hasPlannedTrain
Indicates that an entity is associated with a train that is scheduled or planned to operate, rather than one currently in service.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d50b308190a255874a9b8f3cd3 |
completed | April 19, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69e3b021a5bc81909ae55406f9d0b37f |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:43 a.m.