Triple
T13257787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patricia Velásquez |
E315706
|
entity |
| Predicate | modeledFor |
P2006
|
FINISHED |
| Object | MaxMara |
E835881
|
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: MaxMara | Statement: [Patricia Velásquez, modeledFor, MaxMara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MaxMara Context triple: [Patricia Velásquez, modeledFor, MaxMara]
-
A.
Max Mara
chosen
Max Mara is an Italian luxury fashion house renowned for its high-quality, minimalist womenswear and iconic tailored coats.
-
B.
Liu Jo
Liu Jo is an Italian fashion brand known for its contemporary women’s clothing, denim, and accessories.
-
C.
Etro
Etro is an Italian luxury fashion house renowned for its vibrant prints, paisley patterns, and eclectic, bohemian-inspired designs.
-
D.
Armani
Armani is a renowned Italian luxury fashion house celebrated worldwide for its elegant, minimalist designs in clothing, accessories, and fragrances.
-
E.
Lemaire
Lemaire is a French surname borne by various notable figures in fields such as sports, politics, and the arts.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f7614fc8190a1cac076d706e9aa |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a4240d881909f0ee898fd272826 |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:25 p.m.