Triple
T15652331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kings Mall Shopping Centre |
E376342
|
entity |
| Predicate | hasEateries |
P4442
|
FINISHED |
| Object | various food and drink outlets |
—
|
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: various food and drink outlets | Statement: [Kings Mall Shopping Centre, hasEateries, various food and drink outlets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEateries Context triple: [Kings Mall Shopping Centre, hasEateries, various food and drink outlets]
-
A.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
B.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
C.
hasRestaurant
chosen
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
D.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
E.
hasRestaurantsAndBars
Indicates that the subject location contains or provides access to both restaurants and bars.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eeed2d48190a7a8a618d90012d0 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.