Triple
T14288346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Plagne |
E354237
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Paradiski |
E1052586
|
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: Paradiski | Statement: [La Plagne, partOf, Paradiski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paradiski Context triple: [La Plagne, partOf, Paradiski]
-
A.
Paradiski
chosen
Paradiski is a major interconnected ski area in the French Alps that links several large resorts, including Les Arcs and La Plagne, into one extensive winter sports domain.
-
B.
Parachi
Parachi is a lesser-known Eastern Iranian language spoken by a small community in parts of Afghanistan.
-
C.
Digras
Digras is a town in the Yavatmal district of Maharashtra, India, known for its agrarian economy and role as a local commercial center.
-
D.
Malcantone
Malcantone is a picturesque hilly region in the Swiss canton of Ticino, known for its chestnut forests, traditional villages, and scenic hiking trails near the Italian border.
-
E.
Pangallo
Pangallo is an Italian-origin surname borne by individuals such as American politician Dominick Pangallo.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de698023288190b1d705235c2b2ca3 |
completed | April 14, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d1e14d4819091c381f96c43c58b |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:11 a.m.