Triple
T798966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Italy |
E17084
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Viareggio |
E123041
|
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: Viareggio | Statement: [Central Italy, containsCity, Viareggio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viareggio Context triple: [Central Italy, containsCity, Viareggio]
-
A.
Viareggio
chosen
Viareggio is a coastal city in Tuscany, Italy, renowned for its seaside resorts and famous annual Carnival.
-
B.
Livorno
Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
-
C.
Calvi
Calvi is a coastal town and popular tourist destination on the northwest coast of the French island of Corsica, known for its historic citadel and scenic bay.
-
D.
Rimini
Rimini is a historic Italian coastal city on the Adriatic Sea, renowned for its beaches, Roman and Renaissance landmarks, and vibrant tourism industry.
-
E.
Bari
Bari is a major port city in southern Italy that served as an important Allied military hub and logistics center during World War II.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7b4d9548190aad5fdf1211cf8cd |
completed | March 1, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac89f270a08190927e07dd71652299 |
completed | March 7, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:38 p.m.