Triple
T28935967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jalan Gatot Subroto |
E730314
|
entity |
| Predicate | typicalTrafficCondition |
P23123
|
FINISHED |
| Object | frequent congestion during peak hours |
—
|
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: frequent congestion during peak hours | Statement: [Jalan Gatot Subroto, typicalTrafficCondition, frequent congestion during peak hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrafficCondition Context triple: [Jalan Gatot Subroto, typicalTrafficCondition, frequent congestion during peak hours]
-
A.
roadTraffic
chosen
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
-
B.
trafficEnvironment
Indicates the surrounding traffic conditions or context in which an entity operates or an event occurs.
-
C.
laneCondition
Indicates the state or quality of a lane, such as its usability, surface condition, or any factors affecting how it can be used.
-
D.
majorTrafficType
Indicates the primary kind of traffic or flow that predominantly characterizes a given route, segment, or transportation context.
-
E.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
- 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_69f043ea0aa88190a25acbf46157995a |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_6a013d7180d08190b76f64cb430af9e1 |
completed | May 11, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_6a013c77d23c8190bb59e458b506d6e9 |
completed | May 11, 2026, 2:18 a.m. |
Created at: April 28, 2026, 8:32 a.m.