Triple
T5761186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Route 141 (Peachtree Parkway) near Cumming |
E127096
|
entity |
| Predicate | trafficPattern |
P29452
|
FINISHED |
| Object | peak-hour congestion |
—
|
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: peak-hour congestion | Statement: [State Route 141 (Peachtree Parkway) near Cumming, trafficPattern, peak-hour congestion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficPattern Context triple: [State Route 141 (Peachtree Parkway) near Cumming, trafficPattern, peak-hour congestion]
-
A.
trafficType
Indicates the category or nature of traffic involved in a given interaction, flow, or connection (e.g., type of network, data, or transport traffic).
-
B.
hasTrafficPattern
chosen
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
-
C.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
D.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
E.
travelPattern
Indicates the typical routes, frequencies, and behaviors associated with how an entity moves or travels between 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_69c00833a3fc81908f4bc29ed011b7a6 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02939b22c81908f8354ab175d168d |
completed | March 22, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69c021cc68648190bb86d049ebe80f12 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:49 p.m.