Triple
T36718908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miskolctapolca district |
E906990
|
entity |
| Predicate | partOfTourismSector |
P33155
|
FINISHED |
| Object | Miskolc tourism |
—
|
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: Miskolc tourism | Statement: [Miskolctapolca district, partOfTourismSector, Miskolc tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfTourismSector Context triple: [Miskolctapolca district, partOfTourismSector, Miskolc tourism]
-
A.
hasTourismIndustry
Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
-
B.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
C.
hasTourismFunction
chosen
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
D.
countryTourismCategory
Indicates the tourism classification or category assigned to a country based on its tourism characteristics or status.
-
E.
tourismAssociation
Indicates that there is an organizational or formal association related to tourism activities, services, or promotion between the involved entities.
- 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_69f76e73ad108190a5241585f2303e9a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a0127c36dc08190b07765756b3d0e1b |
completed | May 11, 2026, 12:50 a.m. |
| PD | Predicate disambiguation | batch_6a0125ef57208190be5b5e761fcae981 |
completed | May 11, 2026, 12:42 a.m. |
Created at: May 3, 2026, 4:12 p.m.