Triple
T6130531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Storrow Drive |
E136705
|
entity |
| Predicate | hasTrafficVolume |
P54842
|
FINISHED |
| Object | heavy commuter 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: heavy commuter traffic | Statement: [Storrow Drive, hasTrafficVolume, heavy commuter traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrafficVolume Context triple: [Storrow Drive, hasTrafficVolume, heavy commuter traffic]
-
A.
hasTrafficPattern
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.
-
B.
hasHeavyTraffic
chosen
Indicates that a location, route, or area is experiencing a high volume of traffic, causing congestion or delays.
-
C.
hasTruckTraffic
Indicates that there is truck-related vehicular movement or flow occurring on or through a specified location or route.
-
D.
hasTrafficRegime
Indicates that a specified traffic control or regulatory system applies to a given road, area, or transport context.
-
E.
cargoTrafficRank
Indicates the relative position of an entity in an ordered list based on the volume or intensity of its cargo traffic.
- 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_69c008a0a37c81908e5b4f879158afb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c4de9c48190b98f67a6251ec1df |
completed | March 22, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c055f19b0c81908be34a00ab218723 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:15 p.m.