Triple
T22871491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praia de Gaibu |
E567206
|
entity |
| Predicate | categoriaTurística |
P1769
|
FINISHED |
| Object | praia de banho e surf |
—
|
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: praia de banho e surf | Statement: [Praia de Gaibu, categoriaTurística, praia de banho e surf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categoriaTurística Context triple: [Praia de Gaibu, categoriaTurística, praia de banho e surf]
-
A.
countryTourismCategory
Indicates the tourism classification or category assigned to a country based on its tourism characteristics or status.
-
B.
tourismType
chosen
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
C.
tourCategory
Indicates the classification or type of a tour (e.g., by theme, style, or purpose) that the tour belongs to.
-
D.
tourismCharacteristic
Indicates that something has a specific feature, quality, or attribute relevant to tourism, such as what makes a place, service, or activity notable or suitable for tourists.
-
E.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f05c688819097ba3d24ea8e52f5 |
completed | April 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_69eed2d8c0608190afef4c4e530c0e2c |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 17, 2026, 3:38 p.m.