Triple
T15650162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comiso Airport |
E376288
|
entity |
| Predicate | nearbyAttraction |
P3449
|
FINISHED |
| Object | Donnalucata |
E546763
|
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: Donnalucata | Statement: [Comiso Airport, nearbyAttraction, Donnalucata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donnalucata Context triple: [Comiso Airport, nearbyAttraction, Donnalucata]
-
A.
Donnalucata
chosen
Donnalucata is a seaside village in southern Sicily, Italy, known for its sandy beaches, fishing tradition, and role as a holiday destination on the Mediterranean coast.
-
B.
Trevigiani
Trevigiani are the inhabitants or natives of Treviso, a city in the Veneto region of northeastern Italy.
-
C.
Casarosa
Casarosa is an Italian surname most notably associated with Enrico Casarosa, the animator and director known for his work at Pixar.
-
D.
Ferentino
Ferentino is a historic hill town in the Lazio region of central Italy, known for its ancient Roman and medieval architecture.
-
E.
Baldovino
Baldovino is an Italian given name, historically used in medieval Europe and related to the name Baldwin.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eeed2d48190a7a8a618d90012d0 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7568028481908caa1e49541bbcf1 |
completed | May 9, 2026, 5:56 p.m. |
Created at: April 10, 2026, 4:15 a.m.