Triple
T13625119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aurora Innovation |
E325557
|
entity |
| Predicate | hasRival |
P1375
|
FINISHED |
| Object | Waymo |
E300866
|
NE 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: Waymo | Statement: [Aurora Innovation, hasRival, Waymo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waymo Context triple: [Aurora Innovation, hasRival, Waymo]
-
A.
Waymo
chosen
Waymo is an autonomous driving technology company, originally a Google self-driving car project, that develops and operates self-driving vehicles and robotaxi services.
-
B.
Zoox
Zoox is an autonomous vehicle company focused on developing self-driving robotaxis and mobility services.
-
C.
General Motors (via Cruise)
General Motors (via Cruise) is the U.S. automaker’s autonomous vehicle subsidiary focused on developing and deploying self-driving car technology.
-
D.
Uber Advanced Technologies Group
Uber Advanced Technologies Group was Uber’s self-driving car research and development division focused on autonomous vehicle technologies.
-
E.
Mobileye
Mobileye is an Israeli technology company specializing in advanced driver-assistance systems and autonomous driving solutions, known for its computer vision and mapping technologies used by major automakers worldwide.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69dbbe9c72c88190be3d7a3f2e96afbc |
completed | April 12, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77fa4c5fc8190bd791f181fce2aa1 |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:50 p.m.