Triple
T26607671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senna |
E667826
|
entity |
| Predicate | portraysOccupationOfSubject |
P153983
|
FINISHED |
| Object | racing driver |
—
|
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: racing driver | Statement: [Senna, portraysOccupationOfSubject, racing driver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysOccupationOfSubject Context triple: [Senna, portraysOccupationOfSubject, racing driver]
-
A.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
B.
portrayedProfessionOfCharacter
chosen
Indicates that one entity is the profession or occupation depicted as being held by a particular character.
-
C.
portraysInWork
Indicates that one entity depicts, represents, or plays the role of another entity within a specific creative work.
-
D.
portrayedByProfession
Indicates that an entity is depicted or represented by someone acting in a specified professional capacity.
-
E.
portrayedInWorkType
Indicates that an entity is depicted or represented within a work of a specified type (such as a film, book, painting, or other creative medium).
- 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_69ee9cfd20348190bb1255d2603efb7a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 27, 2026, 2:15 a.m.