Triple
T10309568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uber Blue |
E241850
|
entity |
| Predicate | statusPeriod |
P93296
|
FINISHED |
| Object | fixed qualification period defined by Uber |
—
|
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: fixed qualification period defined by Uber | Statement: [Uber Blue, statusPeriod, fixed qualification period defined by Uber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusPeriod Context triple: [Uber Blue, statusPeriod, fixed qualification period defined by Uber]
-
A.
statusAtTime
Indicates that an entity has a particular status or condition at a specified point in time.
-
B.
statusAtDay
Indicates the specific status or condition an entity has on a given calendar day.
-
C.
status
Indicates the current condition, state, or standing of an entity within a given context.
-
D.
statusModel
Indicates that an entity is associated with a particular status representation or status-handling model.
-
E.
currentStatusSince
Indicates the point in time since which an entity has held its current status or state.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:47 a.m.