Triple
T9421544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lysaker Bridge |
E227162
|
entity |
| Predicate | railTypeCarried |
P1305
|
FINISHED |
| Object | mainline railway |
—
|
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: mainline railway | Statement: [Lysaker Bridge, railTypeCarried, mainline railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railTypeCarried Context triple: [Lysaker Bridge, railTypeCarried, mainline railway]
-
A.
railCarries
Indicates that a rail or railway system transports or conveys a specified entity from one place to another.
-
B.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
C.
carriageType
Indicates the specific kind or category of carriage associated with or used in relation to an entity.
-
D.
railwayCarriageUsedFor
Indicates that a railway carriage is employed or designated for a particular purpose, function, or type of use.
-
E.
rollingStockType
chosen
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c2651c48190808281779fab49df |
completed | April 1, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.