Triple
T20277599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Foce |
E503056
|
entity |
| Predicate | hasView |
P854
|
FINISHED |
| Object | Monte Amiata |
—
|
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: Monte Amiata | Statement: [La Foce, hasView, Monte Amiata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monte Amiata Context triple: [La Foce, hasView, Monte Amiata]
-
A.
Monte Amiata
chosen
Monte Amiata is a volcanic mountain in southern Tuscany, Italy, known for its forested slopes, ski resorts, and geothermal activity.
-
B.
Monte Cotento
Monte Cotento is a notable mountain peak in central Italy, forming part of the Apennine range within the Simbruini Mountains.
-
C.
Monte Sirente
Monte Sirente is a prominent mountain in Italy’s Abruzzo region, known for its rugged limestone massif and inclusion within the protected Sirente-Velino Regional Park.
-
D.
Monte Giano
Monte Giano is a mountain in the central Apennines of Italy, noted for its panoramic views and proximity to the historic town of Cittareale.
-
E.
Monte San Pietrangeli
Monte San Pietrangeli is a small Italian town in the Marche region known for its traditional footwear industry and historic hilltop setting.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e675e4cdfc81908c7cb4519a7d744b |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 16, 2026, 10:35 a.m.