Triple
T16798589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro de Monserrate |
E408295
|
entity |
| Predicate | hasRestaurantArea |
P124671
|
FINISHED |
| Object | restaurants at the summit |
—
|
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: restaurants at the summit | Statement: [Cerro de Monserrate, hasRestaurantArea, restaurants at the summit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestaurantArea Context triple: [Cerro de Monserrate, hasRestaurantArea, restaurants at the summit]
-
A.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
B.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
C.
hasRestaurantFloors
Indicates that a restaurant occupies or is distributed across a specified number of floors in a building.
-
D.
concessionArea
Indicates that one entity is a designated concession area associated with or located within another entity (such as a venue, facility, or site).
-
E.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2abc430819080c1303eded5f416 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.