Triple
T15187554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sella Ronda ski circuit |
E362914
|
entity |
| Predicate | hasAccessPoint |
P1985
|
FINISHED |
| Object | Ortisei |
E565953
|
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: Ortisei | Statement: [Sella Ronda ski circuit, hasAccessPoint, Ortisei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ortisei Context triple: [Sella Ronda ski circuit, hasAccessPoint, Ortisei]
-
A.
Ortisei
chosen
Ortisei is a picturesque alpine town in northern Italy’s Dolomites, renowned for its skiing, woodcarving tradition, and role as a major tourist hub in Val Gardena.
-
B.
Pinzolo
Pinzolo is a mountain town and ski resort in the Trentino region of northern Italy, known for its access to the Brenta Dolomites and outdoor tourism.
-
C.
Ampezzo
Ampezzo is a town in the Dolomite region of northern Italy known for its Ladin cultural and linguistic heritage.
-
D.
Brunico
Brunico is a historic town and popular tourist center in northern Italy’s Alps, known for its medieval old town, castle, and proximity to the Dolomites.
-
E.
Sauze d'Oulx
Sauze d'Oulx is a well-known Italian Alpine ski resort village in the Piedmont region, popular for its extensive slopes and lively après-ski scene.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067995fc8190b048f15086bd42f0 |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed32e425c819083f10f947c258a9b |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 3:09 a.m.