Triple
T32050823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bantigue Sandbar |
E818488
|
entity |
| Predicate | tourismActivityType |
P1769
|
FINISHED |
| Object | day trip destination |
—
|
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: day trip destination | Statement: [Bantigue Sandbar, tourismActivityType, day trip destination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismActivityType Context triple: [Bantigue Sandbar, tourismActivityType, day trip destination]
-
A.
tourismType
chosen
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
B.
tourismEvent
Indicates an event or activity that is organized for or significantly involves tourism, attracting visitors for leisure, cultural, or recreational purposes.
-
C.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
D.
touringActivity
Indicates an activity where an entity travels from place to place, typically for visiting, performing, or sightseeing purposes.
-
E.
countryTourismCategory
Indicates the tourism classification or category assigned to a country based on its tourism characteristics or status.
- 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_69f348fcfb648190859f6be5e04b7cfe |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b4c9c30c81909653ee4e774e4824 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b154b3dc819087115f5f63f7b00f |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:20 a.m.