Triple
T10456851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thai–Lao Friendship Bridge |
E246571
|
entity |
| Predicate | trafficDirectionInLaos |
P3915
|
FINISHED |
| Object | right-hand traffic |
—
|
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: right-hand traffic | Statement: [Thai–Lao Friendship Bridge, trafficDirectionInLaos, right-hand traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficDirectionInLaos Context triple: [Thai–Lao Friendship Bridge, trafficDirectionInLaos, right-hand traffic]
-
A.
trafficDirection
chosen
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
B.
touristTraffic
Indicates the level, flow, or intensity of tourists visiting or moving through a particular place or area.
-
C.
travelTimeFromAoNang
Indicates the amount of time required to travel from Ao Nang to another specified location or entity.
-
D.
roadTraffic
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
-
E.
cargoTrafficRankInFrance
Indicates the ranking position of an entity based on the volume of cargo traffic it handles within France.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe498a808190b88530f0221df4a6 |
completed | April 7, 2026, 12:53 p.m. |
| PD | Predicate disambiguation | batch_69d4fb7d353c8190a73f439a956c7606 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:18 p.m.