Triple
T22777439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ziegelgraben Bridge |
E563740
|
entity |
| Predicate | railwayCarries |
P69331
|
FINISHED |
| Object | rail traffic |
—
|
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: rail traffic | Statement: [Ziegelgraben Bridge, railwayCarries, rail traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayCarries Context triple: [Ziegelgraben Bridge, railwayCarries, rail traffic]
-
A.
railCarries
chosen
Indicates that a rail or railway system transports or conveys a specified entity from one place to another.
-
B.
railwayCarriageUsedFor
Indicates that a railway carriage is employed or designated for a particular purpose, function, or type of use.
-
C.
passengerRollingStock
Indicates that the rolling stock is designed or used for carrying passengers rather than freight or other purposes.
-
D.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
E.
vehiclesPerTrain
Indicates the number of vehicles that are attached to or make up a single train.
- 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_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b6260a8819080e57481281dfe40 |
completed | April 29, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:28 p.m.