Triple
T10063070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Val d’Orcia |
E213033
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Radicofani |
E848532
|
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: Radicofani | Statement: [Val d’Orcia, containsSettlement, Radicofani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radicofani Context triple: [Val d’Orcia, containsSettlement, Radicofani]
-
A.
Radicofani
chosen
Radicofani is a historic hilltop town in Tuscany, central Italy, renowned for its medieval fortress overlooking the Val d'Orcia.
-
B.
Rosciano
Rosciano is a small Italian municipality in the Abruzzo region, known for its rural landscape and traditional local agriculture.
-
C.
Cascia
Cascia is a historic hill town and pilgrimage site in the Umbria region of central Italy, best known for its association with Saint Rita of Cascia.
-
D.
Camporosso
Camporosso is a small Italian town in the Liguria region, near the French border and the Riviera coastline.
-
E.
Loiano
Loiano is a small Italian town in the Emilia-Romagna region, known for its Apennine hillside setting and astronomical observatory.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcfd4e4ac8190a37061b4082caa48 |
completed | April 2, 2026, 2:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6528677f88190b259d5a25ddc290b |
completed | April 8, 2026, 1:05 p.m. |
Created at: March 30, 2026, 8:58 p.m.