Triple
T28794899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saigon–Loc Ninh railway line |
E727057
|
entity |
| Predicate | borderTerminusNearby |
P194246
|
FINISHED |
| Object | Cambodia–Vietnam border |
—
|
NE NERFINISHED |
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: Cambodia–Vietnam border | Statement: [Saigon–Loc Ninh railway line, borderTerminusNearby, Cambodia–Vietnam border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTerminusNearby Context triple: [Saigon–Loc Ninh railway line, borderTerminusNearby, Cambodia–Vietnam border]
-
A.
borderTerminus
Indicates the endpoint location where a border between two areas or entities begins or ends.
-
B.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
C.
nearBorderCrossing
Indicates that an entity is located close to a border crossing point between two regions or countries.
-
D.
nearestInternationalBorderPostAlongPark
Indicates the closest international border checkpoint located along the boundary or within the area of a specified park.
-
E.
borderTradePointWith
Indicates a location or facility where trade or commercial exchange occurs between two bordering regions or countries.
- 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_69f0319b7c44819085736bcc256185e6 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
| PDg | Predicate description generation | batch_69fd68ab21a0819096bfc4a8c14851ad |
completed | May 8, 2026, 4:38 a.m. |
Created at: April 28, 2026, 6:24 a.m.