Triple
T11524936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul–Sydney |
E273267
|
entity |
| Predicate | primaryTrafficFlows |
P27465
|
FINISHED |
| Object | business travel |
—
|
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: business travel | Statement: [Seoul–Sydney, primaryTrafficFlows, business travel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTrafficFlows Context triple: [Seoul–Sydney, primaryTrafficFlows, business travel]
-
A.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
B.
majorTrafficType
chosen
Indicates the primary kind of traffic or flow that predominantly characterizes a given route, segment, or transportation context.
-
C.
traffics
Indicates engaging in the buying, selling, or illicit trading of someone or something, typically as part of an ongoing commercial or criminal operation.
-
D.
hasTrafficDirection
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
E.
facilitatesTrafficFlowBetween
Indicates that one entity enables, supports, or improves the movement of traffic between two other entities or locations.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fd379648190b342e0c4b4f685b7 |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:37 p.m.