Triple
T23129487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praia da Enseada de Bertioga |
E577127
|
entity |
| Predicate | éAdequadaPara |
P18991
|
FINISHED |
| Object | banho de mar |
—
|
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: banho de mar | Statement: [Praia da Enseada de Bertioga, éAdequadaPara, banho de mar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: éAdequadaPara Context triple: [Praia da Enseada de Bertioga, éAdequadaPara, banho de mar]
-
A.
isSuitableFor
chosen
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with another entity.
-
B.
lessSuitableFor
Indicates that one entity is comparatively less appropriate, effective, or fitting than another for a given purpose, context, or condition.
-
C.
intendedForAgeGroup
Indicates that something is designed, suitable, or targeted for use by a specific age group.
-
D.
adaptedTo
Indicates that one entity has been modified, adjusted, or evolved to function effectively within the conditions, requirements, or characteristics defined by another entity.
-
E.
assessesForUseIn
Indicates that one entity evaluates another entity to determine its suitability or appropriateness for a particular use or application.
- 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_69e245f7b0e481909c473ff4e6a54e2c |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e8671f48190887e57d5723e49c1 |
completed | April 29, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4 p.m.