Triple
T15258523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fassa Valley |
E364710
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Pozza di Fassa |
E1142333
|
NE 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: Pozza di Fassa | Statement: [Fassa Valley, hasSettlement, Pozza di Fassa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pozza di Fassa Context triple: [Fassa Valley, hasSettlement, Pozza di Fassa]
-
A.
Gardone Val Trompia
Gardone Val Trompia is a town in the province of Brescia in northern Italy, historically renowned as a major center of firearms manufacturing.
-
B.
Gargnano
Gargnano is a small town on the western shore of Lake Garda in northern Italy, known for its scenic lakeside setting and historic villas.
-
C.
Val di Fassa
Val di Fassa is a renowned valley in the Dolomites of northern Italy, famous for its alpine scenery, ski resorts, and hiking opportunities.
-
D.
Campitello di Fassa
chosen
Campitello di Fassa is a village and ski resort in Italy’s Val di Fassa in the Dolomites, popular for winter sports and alpine tourism.
-
E.
Valsassina
Valsassina is an Alpine valley in the Lombardy region of northern Italy, known for its scenic landscapes, traditional villages, and dairy production.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084d11148190919eef8e55569bb9 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2ce894548190a19bab33285ad165 |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 3:13 a.m.