Triple
T16440829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tibor Kalman |
E399296
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | M&Co |
E954904
|
NE 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: M&Co | Statement: [Tibor Kalman, founded, M&Co]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M&Co Context triple: [Tibor Kalman, founded, M&Co]
-
A.
M&Co
chosen
M&Co was a pioneering New York–based graphic design firm founded by Tibor Kalman, renowned for its influential, concept-driven work in branding, editorial, and album cover design.
-
B.
Inter&Co
Inter&Co is a Brazilian digital financial services company known for offering banking, investment, and insurance products through a unified online platform.
-
C.
Pomellato
Pomellato is an Italian luxury jewelry brand renowned for its colorful gemstone designs and contemporary, handcrafted pieces.
-
D.
Loewe
Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
-
E.
Marchesa
Marchesa is a luxury fashion label renowned for its ornate, red-carpet-ready eveningwear and bridal gowns.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ba7fb0c8190a6a872705cd38987 |
completed | April 18, 2026, 6:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00458dde8881909778c9964ddc8efa |
completed | May 10, 2026, 8:45 a.m. |
Created at: April 10, 2026, 5:10 a.m.