Triple
T31438241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polanco, Mexico City |
E801993
|
entity |
| Predicate | hasLuxuryBrandStores |
P87312
|
FINISHED |
| Object | international fashion brands |
—
|
LITERAL 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: international fashion brands | Statement: [Polanco, Mexico City, hasLuxuryBrandStores, international fashion brands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLuxuryBrandStores Context triple: [Polanco, Mexico City, hasLuxuryBrandStores, international fashion brands]
-
A.
hasLuxuryBrands
Indicates that an entity possesses, offers, or is associated with one or more luxury brands.
-
B.
hasRetailBoutiquesIn
Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
-
C.
hasRetailBrands
Indicates that an entity owns, manages, or is associated with one or more retail brands.
-
D.
hasRetailStores
chosen
Indicates that an entity operates or possesses one or more physical retail store locations.
-
E.
hasJewelleryStores
Indicates that one entity possesses or contains one or more jewellery retail stores associated with it.
- F. None of above.
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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:03 p.m.