Triple
T90901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 14th Street Bridge complex |
E1825
|
entity |
| Predicate | trafficDirection |
P3915
|
FINISHED |
| Object | northbound and southbound |
—
|
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: northbound and southbound | Statement: [14th Street Bridge complex, trafficDirection, northbound and southbound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficDirection Context triple: [14th Street Bridge complex, trafficDirection, northbound and southbound]
-
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.
roadType
Indicates the classification or category of a road based on its functional or physical characteristics.
-
C.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
D.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
E.
transportCorridor
Indicates a route or pathway used to move people, goods, or resources between locations.
- F. None of above. chosen
Provenance (4 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_69a24d1a97dc819094e6c021fe9b05a7 |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24eb82d408190b0f9c786152e8e4c |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a24fed6b8c819080a6c0cd3b16e6bd |
completed | Feb. 28, 2026, 2:16 a.m. |
Created at: Feb. 28, 2026, 2:07 a.m.