Triple
T22488224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowflake |
E555946
|
entity |
| Predicate | routesTrafficThrough |
P148403
|
FINISHED |
| Object | volunteer-run proxy nodes embedded in web browsers |
—
|
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: volunteer-run proxy nodes embedded in web browsers | Statement: [Snowflake, routesTrafficThrough, volunteer-run proxy nodes embedded in web browsers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routesTrafficThrough Context triple: [Snowflake, routesTrafficThrough, volunteer-run proxy nodes embedded in web browsers]
-
A.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
-
B.
roadTraffic
Indicates the presence, flow, or conditions of vehicles and movement along roads or streets.
-
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.
hasTrafficDirection
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
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. 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c3e73108190be5ca89ea96a85e4 |
completed | April 29, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69e898b6eee08190ba673a0ee329e671 |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:49 p.m.