Triple
T19271450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russia–China border |
E481937
|
entity |
| Predicate | crossesTerrain |
P135385
|
FINISHED |
| Object | mountainous terrain |
—
|
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: mountainous terrain | Statement: [Russia–China border, crossesTerrain, mountainous terrain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesTerrain Context triple: [Russia–China border, crossesTerrain, mountainous terrain]
-
A.
crossesMountainRange
Indicates that one entity traverses from one side of a mountain range to the other, passing through or over it.
-
B.
crossesWatershed
Indicates that one entity passes from one drainage basin or watershed area into another, traversing the boundary between them.
-
C.
crossesMountainPass
Indicates that an entity traverses from one side of a mountain range to another via a defined mountain pass.
-
D.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
-
E.
crossesMountainRangeTo
Indicates that one entity traverses from one side of a mountain range to the other, passing across or through it as a route or connection.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbb8bea08190b5c65eebe67dccbb |
completed | April 20, 2026, 10:11 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:29 p.m.