Triple
T1117450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Torre Mayor |
E11132
|
entity |
| Predicate | hasParkingLevels |
P996
|
FINISHED |
| Object | 4 basement levels |
—
|
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: 4 basement levels | Statement: [Torre Mayor, hasParkingLevels, 4 basement levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingLevels Context triple: [Torre Mayor, hasParkingLevels, 4 basement levels]
-
A.
numberOfParkingSpaces
Indicates the total count of parking spaces associated with a particular entity or location.
-
B.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
C.
numberOfBasementLevels
chosen
Indicates the total count of basement levels associated with a given structure or property.
-
D.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
-
E.
numberOfLevels
Indicates the total count of hierarchical layers, stages, or floors associated with an entity.
- 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4562f48190831e959f5f309956 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:43 p.m.