Triple
T22263158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Graves |
E550279
|
entity |
| Predicate | designedFor |
P98
|
FINISHED |
| Object | Alessi |
—
|
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: Alessi | Statement: [Michael Graves, designedFor, Alessi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alessi Context triple: [Michael Graves, designedFor, Alessi]
-
A.
Alessi
chosen
Alessi is an Italian design company renowned for its innovative, playful, and high-quality household products created in collaboration with prominent designers.
-
B.
Comelico
Comelico is a mountainous area in the northeastern Italian Alps, known for its scenic valleys, traditional Ladin culture, and winter sports tourism.
-
C.
Tamburini
Tamburini is an Italian-origin surname borne by various notable figures, including architects, musicians, and designers.
-
D.
Cairoli
Cairoli is an Italian surname most notably associated with Benedetto Cairoli, a 19th-century Italian statesman and patriot.
-
E.
Guidoni
Guidoni is an Italian surname most notably associated with Umberto Guidoni, an astronaut and astrophysicist who flew on NASA Space Shuttle missions.
- 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141b94a688190b17c55477993a745 |
completed | April 28, 2026, 11:24 p.m. |
Created at: April 16, 2026, 8:39 p.m.