Triple
T33181947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aldo Costa |
E849351
|
entity |
| Predicate | roleAtMercedes |
P180370
|
FINISHED |
| Object | engineering director |
—
|
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: engineering director | Statement: [Aldo Costa, roleAtMercedes, engineering director]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtMercedes Context triple: [Aldo Costa, roleAtMercedes, engineering director]
-
A.
roleWithinDaimler
Indicates that one entity holds or has held a specific role, position, or function within the Daimler organization.
-
B.
roleInToyota
Indicates that one entity holds a specific role, position, or function within the organization Toyota.
-
C.
roleAtFerrari
Indicates that an entity holds or held a specific role or position within the Ferrari organization.
-
D.
roleInToyotaGroup
Indicates that an entity holds a specific role or position within the organizational structure of the Toyota Group.
-
E.
roleInTesla
Indicates that one entity holds or held a specific role, position, or function within the organization Tesla.
- 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_69f3495d06508190b0b7729982982cea |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
| PDg | Predicate description generation | batch_69f73adfd9a081908adae6bd59dfefb9 |
completed | May 3, 2026, 12:09 p.m. |
Created at: May 1, 2026, 1:29 a.m.