Triple
T19276495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dogana–Rimini road crossing |
E482070
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Dogana |
—
|
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: Dogana | Statement: [Dogana–Rimini road crossing, connects, Dogana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dogana Context triple: [Dogana–Rimini road crossing, connects, Dogana]
-
A.
Dogana
chosen
Dogana is a major town and commercial hub in northeastern San Marino, located near the border with Italy.
-
B.
Tigana
Tigana is a French former professional footballer and manager, best known as a dynamic midfielder for clubs like Bordeaux and the French national team during the 1980s.
-
C.
Duryudana
Duryudana is the Javanese rendition of Duryodhana, the principal Kaurava antagonist from the Mahabharata, adapted into local wayang and literary traditions.
-
D.
Doliana
Doliana is a village in the municipality of North Kynouria in the Arcadia regional unit of the Peloponnese, Greece.
-
E.
Gannushkina
Gannushkina is a Russian surname most notably associated with Svetlana Gannushkina, a prominent human rights activist and mathematician.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbbd5f34819086535f28fd880411 |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:29 p.m.