Triple
T28982216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakeside neighborhood |
E734581
|
entity |
| Predicate | shoppingAccess |
P166903
|
FINISHED |
| Object | proximity to retail and commercial areas |
—
|
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: proximity to retail and commercial areas | Statement: [Lakeside neighborhood, shoppingAccess, proximity to retail and commercial areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shoppingAccess Context triple: [Lakeside neighborhood, shoppingAccess, proximity to retail and commercial areas]
-
A.
shoppingFeature
Indicates that an entity provides or supports a shopping-related capability, option, or functionality for another entity.
-
B.
shoppingStyle
Indicates the manner or approach an entity typically uses when shopping, such as their preferred methods, habits, or decision-making style.
-
C.
shopSection
Indicates the specific section or area within a shop where an item, activity, or service is located or takes place.
-
D.
hasShoppingMall
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
E.
isShoppingDestination
Indicates that a place serves as a primary location where people go to shop for goods or services.
- F. None of above. chosen
Provenance (4 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_69f05b0dd9b481908b7901e1c95ff6b2 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f664aa283c8190a869d0555eff60c6 |
completed | May 2, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f6645a615481909b53d94512ecbaf1 |
completed | May 2, 2026, 8:53 p.m. |
Created at: April 28, 2026, 9:12 a.m.