Triple
T34603211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pegswood railway station |
E888521
|
entity |
| Predicate | hasServiceOperatorType |
P193920
|
FINISHED |
| Object | train operating company |
—
|
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: train operating company | Statement: [Pegswood railway station, hasServiceOperatorType, train operating company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceOperatorType Context triple: [Pegswood railway station, hasServiceOperatorType, train operating company]
-
A.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
B.
hasBusServiceOperatorType
chosen
Indicates that a bus service is associated with a specific type or category of operator responsible for running it.
-
C.
typicalOperatorService
Indicates that an entity commonly performs or provides a particular operational service in a standard or expected manner.
-
D.
hasOperationType
Indicates the specific kind or category of operation associated with an entity or process.
-
E.
hasPeakServiceType
Indicates that an entity is associated with a specific type or category of service provided during peak periods.
- 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_69f349d489d48190ba30e7d97c6f5ef9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffde9263248190996f970b6cf6e49d |
completed | May 10, 2026, 1:25 a.m. |
| PD | Predicate disambiguation | batch_69ffdd760f1c8190abc6c0c1cd97ba5f |
completed | May 10, 2026, 1:20 a.m. |
Created at: May 1, 2026, 2:03 a.m.