Triple
T31895973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uber driver-partners |
E814282
|
entity |
| Predicate | mayOrganizeAs |
P4786
|
FINISHED |
| Object | driver associations |
—
|
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: driver associations | Statement: [Uber driver-partners, mayOrganizeAs, driver associations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayOrganizeAs Context triple: [Uber driver-partners, mayOrganizeAs, driver associations]
-
A.
mayBeOrganizedBy
Indicates that an event, activity, or entity has the possibility of being organized or arranged by a particular agent or organization, without asserting that this organization definitely occurs.
-
B.
alsoOrganized
Indicates that the same entity was additionally responsible for organizing another related event, activity, or entity.
-
C.
organizes
Indicates that one entity arranges, coordinates, or structures activities, items, or people into an ordered or planned form for a particular purpose.
-
D.
organizedAt
Indicates that an event or activity was arranged, planned, or hosted at a specific location or venue.
-
E.
organizedAs
chosen
Indicates how elements are structured, arranged, or grouped according to a particular organizing principle or scheme.
- 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_69f348ef817481908440e2250319bcc8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b1647918819085ec718e13f9926a |
completed | May 3, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:58 p.m.