Triple
T15183646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hồng Hà |
E362810
|
entity |
| Predicate | transboundaryRiverBetween |
P93095
|
FINISHED |
| Object | China and Vietnam |
—
|
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: China and Vietnam | Statement: [Hồng Hà, transboundaryRiverBetween, China and Vietnam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transboundaryRiverBetween Context triple: [Hồng Hà, transboundaryRiverBetween, China and Vietnam]
-
A.
transboundaryRiverOf
chosen
Indicates that a river crosses or forms the boundary between two or more political or administrative regions.
-
B.
transboundaryBasin
Indicates that a river basin or watershed extends across and is shared by the territories of two or more political or administrative jurisdictions.
-
C.
betweenRiver
Indicates a spatial relationship where something is located in the area separating two rivers or lies in the intermediate region defined by them.
-
D.
locatedBetweenRivers
Indicates that something is situated in the area or region bounded or flanked by two rivers.
-
E.
associatedRiverBasin
Indicates that one entity is linked to, or lies within the drainage area of, a particular river basin.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006674c088190ba635a78c30f5637 |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:09 a.m.