Triple
T15505885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schuylkill Expressway |
E379079
|
entity |
| Predicate | trafficIssue |
P4588
|
FINISHED |
| Object | recurring 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: recurring peak-hour congestion | Statement: [Schuylkill Expressway, trafficIssue, recurring peak-hour congestion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficIssue Context triple: [Schuylkill Expressway, trafficIssue, recurring peak-hour congestion]
-
A.
roadTraffic
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
-
B.
roadAffected
Indicates that a road is impacted or disrupted by a condition, event, or action, such as construction, accidents, or adverse weather.
-
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.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
E.
trafficLevel
chosen
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcd5d948190b25a67a72ef980e9 |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2896a9c8190a8b9627deb3c17b4 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:55 a.m.