Triple
T8358733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inner Banks |
E196746
|
entity |
| Predicate | tourismRegionType |
P3030
|
FINISHED |
| Object | branding region |
—
|
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: branding region | Statement: [Inner Banks, tourismRegionType, branding region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismRegionType Context triple: [Inner Banks, tourismRegionType, branding region]
-
A.
tourismRegion
chosen
Indicates that a place or area is designated or recognized as a tourism region associated with another geographic or administrative entity.
-
B.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
C.
typicalDestinationsRegion
Indicates that a region is a common or characteristic destination area associated with something (such as travelers, routes, or activities).
-
D.
connectsToTouristRegion
Indicates that one entity has a direct linkage or association to a tourist region, such as through location, access, or service provision.
-
E.
geographicalRegionType
Indicates the specific kind or category of geographical region that an entity belongs to (e.g., continent, country, province, or city).
- 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_69ca82f08b348190bfb7881944bbff6f |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb806fa5c88190b23b6b3ee9d6ec6d |
completed | March 31, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69cb70ca25548190b0f90c5384e3fb3c |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:59 p.m.