Triple
T15029426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanzhou railway station |
E378302
|
entity |
| Predicate | railwayStationClassification |
P103205
|
FINISHED |
| Object | Top-class station |
—
|
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: Top-class station | Statement: [Lanzhou railway station, railwayStationClassification, Top-class station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayStationClassification Context triple: [Lanzhou railway station, railwayStationClassification, Top-class station]
-
A.
railwayStationCategory
Indicates the classification or type category assigned to a railway station within a rail network or system.
-
B.
railwayStationRank
chosen
Indicates the relative importance or classification level assigned to a railway station within a railway network or system.
-
C.
railwayStationInstanceOf
Indicates that a given railway station is an instance of a specified class or type of railway station.
-
D.
railwayStationFunction
Indicates that an entity serves as a railway station and specifies the role or function it performs within the railway network.
-
E.
isRailwayStation
Indicates that the subject is a railway station, i.e., a facility where trains regularly stop to pick up or drop off passengers and/or freight.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e0e8c88190ac6f5786b4d4040f |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:59 a.m.