Triple
T27017248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verbanesi |
E680567
|
entity |
| Predicate | associatedWithRegionCulture |
P1439
|
FINISHED |
| Object | Piedmontese culture |
—
|
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: Piedmontese culture | Statement: [Verbanesi, associatedWithRegionCulture, Piedmontese culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithRegionCulture Context triple: [Verbanesi, associatedWithRegionCulture, Piedmontese culture]
-
A.
namedForCulturalRegion
Indicates that something is given a name derived from or honoring a specific cultural region.
-
B.
culturalRegion
Indicates that an entity is located in, associated with, or belongs to a specific cultural region or cultural area.
-
C.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
D.
hasAssociatedCulture
chosen
Indicates that an entity is related to, influenced by, or characterized by a particular culture.
-
E.
subjectLanguageRegion
Indicates that the subject is associated with or uses a language specific to a particular geographic region.
- 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_69eeeb5450988190bfc9a3c012ac463a |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69ff9b1ad27081908f8a492396950795 |
completed | May 9, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69ff9a6354c48190ae21070c1424cb7a |
completed | May 9, 2026, 8:34 p.m. |
Created at: April 27, 2026, 7:06 a.m.