Triple
T24625093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrade border crossing |
E609516
|
entity |
| Predicate | facilitatesTrafficType |
P621
|
FINISHED |
| Object | vehicle 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: vehicle traffic | Statement: [Andrade border crossing, facilitatesTrafficType, vehicle traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facilitatesTrafficType Context triple: [Andrade border crossing, facilitatesTrafficType, vehicle traffic]
-
A.
coversTrafficType
Indicates that one entity includes, handles, or applies to a specified type or category of traffic.
-
B.
facilitatesTrafficFlowBetween
Indicates that one entity enables, supports, or improves the movement of traffic between two other entities or locations.
-
C.
majorTrafficType
Indicates the primary kind of traffic or flow that predominantly characterizes a given route, segment, or transportation context.
-
D.
trafficType
chosen
Indicates the category or nature of traffic involved in a given interaction, flow, or connection (e.g., type of network, data, or transport traffic).
-
E.
relievesTrafficFrom
Indicates that one entity reduces or alleviates traffic congestion that would otherwise occur on another entity.
- 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_69e2c4d1d3708190a0f2dc6a3a8523bb |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:32 a.m.