Triple
T15009973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenox Square |
E377809
|
entity |
| Predicate | hasLuxuryRetailer |
P94000
|
FINISHED |
| Object | Prada |
E31748
|
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: Prada | Statement: [Lenox Square, hasLuxuryRetailer, Prada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prada Context triple: [Lenox Square, hasLuxuryRetailer, Prada]
-
A.
Prada
chosen
Prada is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and accessories.
-
B.
Prada
Prada is a small commune in the Pyrénées-Orientales department of southern France, known for its Catalan cultural heritage and scenic location in the Têt River valley.
-
C.
Gucci
Gucci is a renowned Italian luxury fashion house known for its high-end clothing, accessories, and iconic branding.
-
D.
Fendi
Fendi is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and iconic handbags.
-
E.
Louis Vuitton
Louis Vuitton is a French luxury fashion house and brand renowned worldwide for its high-end leather goods, ready-to-wear, accessories, and iconic monogram designs.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded734943481908dad4ceed4fe850c |
completed | April 15, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae080ef88190a26c4f9b1675f9de |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 2:55 a.m.