Triple
T22385659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italdesign Giugiaro |
E553387
|
entity |
| Predicate | designedFor |
P98
|
FINISHED |
| Object | Seat |
—
|
NE NERFINISHED |
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: Seat | Statement: [Italdesign Giugiaro, designedFor, Seat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seat Context triple: [Italdesign Giugiaro, designedFor, Seat]
-
A.
Seat
chosen
SEAT is a Spanish automobile manufacturer known for producing a range of affordable, stylish cars within the Volkswagen Group.
-
B.
Window Seat
"Window Seat" is a neo-soul single by Erykah Badu, known for its mellow, introspective vibe and its controversial, symbolism-rich music video.
-
C.
Love Seat
"Love Seat" is an EP by the indie pop band The Softies, showcasing their gentle, melancholic melodies and intimate lo-fi sound.
-
D.
Sitton
Sitton is a surname of English origin borne by various notable individuals, including athletes and public figures.
-
E.
Chair X
Chair X is one of the numbered academic seats of the Royal Spanish Academy, occupied by a distinguished scholar responsible for contributing to the institution’s work on the Spanish language.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582f5f348190881df0d5af110aef |
completed | April 29, 2026, 1 a.m. |
Created at: April 16, 2026, 8:45 p.m.