Triple
T38030134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dausa railway station |
E948884
|
entity |
| Predicate | hasMailTrains |
—
|
GENERATED |
| Object | yes |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMailTrains Context triple: [Dausa railway station, hasMailTrains, yes]
-
A.
hasTrains
Indicates that one entity possesses, operates, or is served by one or more trains in relation to another entity or context.
-
B.
hasLNGTrain
Indicates that something possesses or is equipped with an LNG (liquefied natural gas) processing or transport train as part of its facilities or infrastructure.
-
C.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
D.
hasTailTrain
Indicates that one entity possesses or is characterized by a tail-like train extending from it.
-
E.
hasTramTrainLine
Indicates that there exists a tram-train line connection or service linking the related entities.
- F. None of above. chosen
Provenance (1 batch)
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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
Created at: May 3, 2026, 4:20 p.m.