Triple
T32524650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Vista |
E831275
|
entity |
| Predicate | hasShoppingAreaNearby |
P16039
|
FINISHED |
| Object | Fashion Valley Mall |
—
|
NE NERFINISHED |
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: Fashion Valley Mall | Statement: [Linda Vista, hasShoppingAreaNearby, Fashion Valley Mall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoppingAreaNearby Context triple: [Linda Vista, hasShoppingAreaNearby, Fashion Valley Mall]
-
A.
hasShoppingDistrict
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
-
B.
hasConvenienceStore
Indicates that one entity possesses, contains, or is associated with a convenience store.
-
C.
hasShoppingDistrictType
Indicates that an entity is associated with a particular type or category of shopping district.
-
D.
hasShoppingMall
chosen
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
E.
hasInformalMarketNearby
Indicates that an entity is located close to an informal or unregulated market area.
- 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_69f34923e1548190be0524205d8cdf8f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: May 1, 2026, 1:01 a.m.