Triple
T33181949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aldo Costa |
E849351
|
entity |
| Predicate | careerStartField |
P24248
|
FINISHED |
| Object | motorsport engineering |
—
|
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: motorsport engineering | Statement: [Aldo Costa, careerStartField, motorsport engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerStartField Context triple: [Aldo Costa, careerStartField, motorsport engineering]
-
A.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
B.
careerField
chosen
Indicates the professional domain or occupational area in which an entity works or specializes.
-
C.
careerStartAs
Indicates the role, position, or occupation in which an individual first began their professional career.
-
D.
studCareerBegan
Indicates that a student's professional or academic career started at a specified time or institution.
-
E.
studCareerStart
Indicates the point in time when a student's professional or academic career begins.
- 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_69f3495d06508190b0b7729982982cea |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:29 a.m.