Triple
T8088789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa de la Cocina |
E188801
|
entity |
| Predicate | hasNoiseLevel |
P32166
|
FINISHED |
| Object | quiet |
—
|
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: quiet | Statement: [Playa de la Cocina, hasNoiseLevel, quiet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoiseLevel Context triple: [Playa de la Cocina, hasNoiseLevel, quiet]
-
A.
hasNoisePerformance
Indicates the degree to which one entity’s operation or behavior produces or is characterized by a certain level or quality of noise.
-
B.
noiseLevel
chosen
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
C.
hasNoiseTerm
Indicates that a given expression, model, or equation includes an additional noise term representing random or unexplained variation.
-
D.
noiseCompliance
Indicates that an entity adheres to specified rules or standards governing acceptable noise levels or sound emissions.
-
E.
targetsNoiseType
Indicates that an entity is directed at, designed for, or specifically affects a particular type or category of noise.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb421c717c819089dd88c30a6401aa |
completed | March 31, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.