Triple
T33325472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vipiteno |
E853250
|
entity |
| Predicate | borderRegionCulture |
P1968
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [Vipiteno, borderRegionCulture, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderRegionCulture Context triple: [Vipiteno, borderRegionCulture, Italian]
-
A.
borderCultureWith
Indicates that two regions or entities share a common boundary across which cultural traits, practices, or influences are actively exchanged or intertwined.
-
B.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
C.
culturalRegion
chosen
Indicates that an entity is located in, associated with, or belongs to a specific cultural region or cultural area.
-
D.
borderRegionOf
Indicates that one region lies along, touches, or forms part of the boundary of another region.
-
E.
borderDialectOf
Indicates a dialect that is spoken in a border area and is linguistically associated with or derived from a particular neighboring language or dialect.
- 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff370698ec81909bb1596d7d4112ba |
completed | May 9, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69ff3699b6288190b564839cb05f5cf6 |
completed | May 9, 2026, 1:28 p.m. |
Created at: May 1, 2026, 1:33 a.m.