Triple
T18210846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester Designer Outlets |
E436026
|
entity |
| Predicate | hasApproximateNumberOfStores |
P8902
|
FINISHED |
| Object | dozens of outlet stores |
—
|
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: dozens of outlet stores | Statement: [Manchester Designer Outlets, hasApproximateNumberOfStores, dozens of outlet stores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfStores Context triple: [Manchester Designer Outlets, hasApproximateNumberOfStores, dozens of outlet stores]
-
A.
numberOfStores
chosen
Indicates the total count of stores associated with a given entity or context.
-
B.
hasRetailStores
Indicates that an entity operates or possesses one or more physical retail store locations.
-
C.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
-
D.
hasStoreLocation
Indicates that an entity operates or maintains a store at a specified physical location.
-
E.
hasNotableStore
Indicates that an entity operates or is associated with a store that is considered notable or significant in some way.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e228a7fc81909cfcf11cf7ce1360 |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.