Triple
T20181389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monte Rosa region |
E492734
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Valsesia |
—
|
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: Valsesia | Statement: [Monte Rosa region, contains, Valsesia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valsesia Context triple: [Monte Rosa region, contains, Valsesia]
-
A.
Valsesia
chosen
Valsesia is a scenic alpine valley in Italy’s Piedmont region, known for its mountain landscapes, outdoor sports, and traditional villages.
-
B.
Lunigiana
Lunigiana is a historical region in northwestern Italy, spanning parts of Tuscany and Liguria, known for its medieval castles, hilltop villages, and rugged Apennine landscapes.
-
C.
Valdera
Valdera is a hilly area in the province of Pisa, Tuscany, known for its rural landscapes, small historic towns, and agricultural traditions.
-
D.
Valdelsa
Valdelsa is a historical valley area in Tuscany, Italy, known for its medieval hill towns, agricultural landscapes, and cultural heritage.
-
E.
Campidanesu
Campidanesu is the native name for Campidanese Sardinian, a major dialect of the Sardinian language spoken in southern Sardinia.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668eed2e88190b54b15e6545dbdf8 |
completed | April 20, 2026, 5:57 p.m. |
Created at: April 11, 2026, 11:36 p.m.