Triple
T20510506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sopraceneri |
E503544
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Biasca |
—
|
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: Biasca | Statement: [Sopraceneri, contains, Biasca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biasca Context triple: [Sopraceneri, contains, Biasca]
-
A.
Biasca
chosen
Biasca is a town in the canton of Ticino in southern Switzerland, known as a regional hub in the Italian-speaking part of the country.
-
B.
Biasone
Biasone is an Italian surname most notably associated with Danny Biasone, the basketball executive credited with creating the NBA’s 24-second shot clock.
-
C.
Bottidda
Bottidda is a small municipality in the historical Logudoro region of central-northern Sardinia, Italy.
-
D.
Biainili
Biainili is the native name for the ancient kingdom of Urartu, an Iron Age state centered around Lake Van in the Armenian Highlands.
-
E.
Biase
Biase is a local government area in southeastern Nigeria known for its diverse ethnic communities and agricultural activities within Cross River State.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dcab8248190992e6ada23e5f253 |
completed | April 20, 2026, 9:42 p.m. |
Created at: April 16, 2026, 11:36 a.m.