Triple
T38345895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charjew |
E1041537
|
entity |
| Predicate | crossesBorderVia |
P192100
|
FINISHED |
| Object | bridges over Amu Darya |
—
|
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: bridges over Amu Darya | Statement: [Charjew, crossesBorderVia, bridges over Amu Darya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesBorderVia Context triple: [Charjew, crossesBorderVia, bridges over Amu Darya]
-
A.
crossesBorderOf
Indicates that one entity passes from one side of the boundary of another entity (typically a region or area) to the other side, traversing its border.
-
B.
hasBorderCrossing
Indicates that there exists a point or facility where movement or transit is possible between the boundaries of two adjacent regions or jurisdictions.
-
C.
crossesInternationalBoundaryAt
Indicates that one entity passes from one country’s territory into another at a specific boundary location.
-
D.
crossesBorderRiver
chosen
Indicates that one entity moves from one side of a border-defining river to the other, traversing the river that serves as a boundary.
-
E.
borderTownAcrossBorder
Indicates that a town lies on one side of a border directly opposite or adjacent to a town on the other side of that border.
- 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_69f76e2ad95481908c920c0e5c1c3e26 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: May 3, 2026, 4:30 p.m.