Triple
T6285860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iberian gauge |
E140896
|
entity |
| Predicate | railwayNetworkType |
P18634
|
FINISHED |
| Object | conventional network in Spain |
—
|
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: conventional network in Spain | Statement: [Iberian gauge, railwayNetworkType, conventional network in Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayNetworkType Context triple: [Iberian gauge, railwayNetworkType, conventional network in Spain]
-
A.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
B.
railSystemType
chosen
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
C.
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.
-
D.
hasRailwayInfrastructureType
Indicates that an entity possesses or is associated with a specific type or category of railway infrastructure.
-
E.
railNetworkRole
Indicates the specific function or responsibility an entity has within a rail network system.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063fe59fc81908dbd968017771190 |
completed | March 22, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69c0560a0270819098ad2785b91e8f39 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:26 p.m.