Triple
T20276840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Affi |
E503037
|
entity |
| Predicate | isLocatedNear |
P350
|
FINISHED |
| Object | Bardolino |
—
|
NE NERFINISHED |
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: Bardolino | Statement: [Affi, isLocatedNear, Bardolino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bardolino Context triple: [Affi, isLocatedNear, Bardolino]
-
A.
Bardolino
chosen
Bardolino is a picturesque Italian town in the Veneto region, renowned for its lakeside setting on Lake Garda and its namesake red wine.
-
B.
Valpolicella
Valpolicella is a renowned wine-producing area in Italy’s Veneto region, famous for its red wines including Amarone and Ripasso.
-
C.
Soave
Soave is a historic Italian town in the Veneto region, renowned for its medieval castle and as the namesake of a famous white wine.
-
D.
Lambrusco wine
Lambrusco wine is a lightly sparkling Italian red wine, typically fruity and refreshing, traditionally produced in the Emilia-Romagna region.
-
E.
Negrar di Valpolicella
Negrar di Valpolicella is a municipality in Italy’s Veneto region, renowned for its vineyards and production of Valpolicella wines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e675e3df68819096fb859bc92a0da1 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 16, 2026, 10:35 a.m.