Triple
T38276750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parnas railway station |
E1021980
|
entity |
| Predicate | hasRailwayTrafficType |
P196410
|
FINISHED |
| Object | passenger 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: passenger traffic | Statement: [Parnas railway station, hasRailwayTrafficType, passenger traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailwayTrafficType Context triple: [Parnas railway station, hasRailwayTrafficType, passenger traffic]
-
A.
hasRailwayInfrastructureType
Indicates that an entity possesses or is associated with a specific type or category of railway infrastructure.
-
B.
hasRailwayTraction
Indicates that a railway system, line, or vehicle uses a specified type or method of traction (e.g., electric, diesel, steam) for its propulsion.
-
C.
hasCargoTrafficType
Indicates that an entity is associated with a specific type or category of cargo traffic it handles or supports.
-
D.
isRailwayIn
Indicates that a railway is located within or passes through a specified geographic or administrative area.
-
E.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
- F. None of above. chosen
Provenance (4 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69fe30bb07d08190877539d5aa202d24 |
completed | May 8, 2026, 6:51 p.m. |
Created at: May 3, 2026, 4:30 p.m.