Triple
T8211103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grizzly River Run |
E191816
|
entity |
| Predicate | usesVirtualQueue |
P79890
|
FINISHED |
| Object | no regular virtual queue |
—
|
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: no regular virtual queue | Statement: [Grizzly River Run, usesVirtualQueue, no regular virtual queue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVirtualQueue Context triple: [Grizzly River Run, usesVirtualQueue, no regular virtual queue]
-
A.
usesQueue
chosen
Indicates that one entity employs or relies on a queue mechanism to manage or process items, tasks, or messages.
-
B.
hasQueue
Indicates that an entity maintains or is associated with a queue, typically representing an ordered list of items or tasks awaiting processing.
-
C.
hasVirtualTransfer
Indicates that one entity is transferred to another through a non-physical or digital/virtual means rather than a direct physical transfer.
-
D.
usedVirtualVoting
Indicates that an entity participated in a voting process through virtual or remote means rather than in person.
-
E.
hasVirtualExperience
Indicates that one entity possesses or has participated in a virtual or digitally simulated experience related to another entity.
- 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_69ca82c8c054819087fedd9a5436b8a3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb76dec42c819090252fe186a68d34 |
completed | March 31, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69cb36ad01ac81909609b15f6a6c8581 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:44 p.m.