Triple
T34548586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shawford railway station |
E886999
|
entity |
| Predicate | servedByTypeOfTrain |
P56947
|
FINISHED |
| Object | electric multiple unit |
—
|
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: electric multiple unit | Statement: [Shawford railway station, servedByTypeOfTrain, electric multiple unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedByTypeOfTrain Context triple: [Shawford railway station, servedByTypeOfTrain, electric multiple unit]
-
A.
servedByNamedTrain
Indicates that a service, route, or journey is operated specifically by a train with a particular designated name.
-
B.
railwayTypeServed
Indicates the type of railway system or service that a given entity (such as a station, line, or facility) is designed to serve or accommodate.
-
C.
servedByRailroad
Indicates that a location or facility is provided with transportation or service by a railroad line or company.
-
D.
trainTypeUsed
chosen
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
E.
railServiceType
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
- 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_69f349cff89081908f91e0b064f4833e |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffbf84f4948190b41a7bba07ae61ec |
completed | May 9, 2026, 11:13 p.m. |
| PD | Predicate disambiguation | batch_69ffbf0a59f88190870dbe25d8a63a00 |
completed | May 9, 2026, 11:11 p.m. |
Created at: May 1, 2026, 2:02 a.m.