Triple
T1162122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Nice |
E24515
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Calvi |
E136975
|
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: Calvi | Statement: [Port of Nice, connectsTo, Calvi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Calvi Context triple: [Port of Nice, connectsTo, Calvi]
-
A.
Calvi
chosen
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.
-
B.
Livorno
Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
-
C.
Viareggio
Viareggio is a coastal city in Tuscany, Italy, renowned for its seaside resorts and famous annual Carnival.
-
D.
Piombino
Piombino is a coastal town and port in Tuscany, Italy, serving as a major mainland gateway to the island of Elba and other Tyrrhenian destinations.
-
E.
Capoliveri
Capoliveri is a historic hilltop town and popular tourist resort on the Italian island of Elba, known for its medieval center and coastal beaches.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcb2bb84819088bd94e91c10fb0c |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1c90c95081908af02d73f7d762ee |
completed | March 8, 2026, 6:52 a.m. |
Created at: March 1, 2026, 7:45 p.m.