Triple
T3865621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanggula Mountains |
E91844
|
entity |
| Predicate | railwayStationElevation |
P41300
|
FINISHED |
| Object | Tanggula railway station about 5068 metres |
—
|
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: Tanggula railway station about 5068 metres | Statement: [Tanggula Mountains, railwayStationElevation, Tanggula railway station about 5068 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayStationElevation Context triple: [Tanggula Mountains, railwayStationElevation, Tanggula railway station about 5068 metres]
-
A.
railwayStationFor
Indicates a relationship where a railway station serves, is designated for, or primarily associated with a particular place, line, or service.
-
B.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
C.
elevationBy
Indicates a relationship where one entity raises, increases, or enhances the level, status, or intensity of another entity.
-
D.
hasAltitudeStation
chosen
Indicates that something is associated with or located at a station characterized by a specific altitude.
-
E.
railwayStationUsage
Indicates how frequently or extensively a railway station is used, such as by measuring passenger numbers, train traffic, or overall activity levels.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3a253c81909df7dc0422ff7989 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.