Triple
T16996343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daimler Buses |
E412323
|
entity |
| Predicate | roleWithinDaimler |
P126095
|
FINISHED |
| Object | bus and coach manufacturing division |
—
|
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: bus and coach manufacturing division | Statement: [Daimler Buses, roleWithinDaimler, bus and coach manufacturing division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleWithinDaimler Context triple: [Daimler Buses, roleWithinDaimler, bus and coach manufacturing division]
-
A.
roleInToyotaGroup
Indicates that an entity holds a specific role or position within the organizational structure of the Toyota Group.
-
B.
roleInToyota
Indicates that one entity holds a specific role, position, or function within the organization Toyota.
-
C.
roleWithinBoeing
Indicates that one entity holds or has held a specific role, position, or function within the organization Boeing.
-
D.
roleInTesla
Indicates that one entity holds or held a specific role, position, or function within the organization Tesla.
-
E.
roleWithinSamsungCT
Indicates a person’s specific role, position, or function within the organization Samsung C&T.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d2879af081909665f9f838bcfbe7 |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e378e037c88190935d732e0f10d5d7 |
completed | April 18, 2026, 12:28 p.m. |
Created at: April 10, 2026, 5:32 a.m.