Triple
T11141680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warszawa Śródmieście railway station |
E263568
|
entity |
| Predicate | railwayTrafficType |
P18634
|
FINISHED |
| Object | suburban |
—
|
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: suburban | Statement: [Warszawa Śródmieście railway station, railwayTrafficType, suburban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayTrafficType Context triple: [Warszawa Śródmieście railway station, railwayTrafficType, suburban]
-
A.
railwayTraffic
Indicates the presence, flow, or management of train movements along railway lines between locations.
-
B.
railwayTrafficDirection
Indicates the customary side of the track on which trains are operated or expected to run within a given railway system or segment.
-
C.
railSystemType
chosen
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
D.
coordinatesRailTrafficWith
Indicates that one entity organizes and synchronizes rail operations or movements with another entity to ensure coordinated train traffic.
-
E.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8623158819096ad1678fa9e72bb |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.