Triple
T29033793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goba |
E737797
|
entity |
| Predicate | tourismService |
P166533
|
FINISHED |
| Object | accommodation for park visitors |
—
|
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: accommodation for park visitors | Statement: [Goba, tourismService, accommodation for park visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismService Context triple: [Goba, tourismService, accommodation for park visitors]
-
A.
tourismModel
Indicates the conceptual framework or approach that defines how tourism activities, services, and interactions are structured and operate within a given context.
-
B.
touristAgency
Indicates that an entity is a travel or tourist agency that organizes or provides tourism-related services for another entity.
-
C.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
D.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
E.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
- F. None of above. chosen
Provenance (4 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6622808b48190bbabcc75288ab031 |
completed | May 2, 2026, 8:44 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f6617a7e7c81908cfac4a2250797ee |
completed | May 2, 2026, 8:41 p.m. |
Created at: April 28, 2026, 9:57 a.m.