Triple
T13625209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uber Advanced Technologies Group |
E325559
|
entity |
| Predicate | notableIncidentYear |
P43898
|
FINISHED |
| Object | 2018 |
—
|
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: 2018 | Statement: [Uber Advanced Technologies Group, notableIncidentYear, 2018]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableIncidentYear Context triple: [Uber Advanced Technologies Group, notableIncidentYear, 2018]
-
A.
notableAccidentYear
chosen
Indicates the year in which a notable accident involving the subject occurred.
-
B.
notableCaseYear
Indicates the year in which a particular case became notable or gained recognized significance.
-
C.
notableProjectYear
Indicates the year in which a notable project associated with an entity took place, was created, or was prominently recognized.
-
D.
notableEventDate
Indicates the date on which a notable or significant event associated with the subject occurred.
-
E.
notableIncidentType
Indicates the specific category or kind of significant event or incident associated with an 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60635d08190899806fe8936f02a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe85e1c4819095194f4b7f9f6118 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:50 p.m.