Triple
T12372283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franco Alfano |
E295031
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Posillipo |
E192215
|
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: Posillipo | Statement: [Franco Alfano, placeOfBirth, Posillipo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Posillipo Context triple: [Franco Alfano, placeOfBirth, Posillipo]
-
A.
Posillipo
chosen
Posillipo is an affluent coastal district of Naples, Italy, known for its scenic cliffs, historic villas, and panoramic views over the Bay of Naples.
-
B.
Monte Mario
Monte Mario is the highest hill in Rome, known for its panoramic views over the city and the River Tiber.
-
C.
Montagnana
Montagnana is a historic walled town in the Veneto region of northern Italy, renowned for its remarkably well-preserved medieval fortifications.
-
D.
Camporosso
Camporosso is a small Italian town in the Liguria region, near the French border and the Riviera coastline.
-
E.
Altomonte
Altomonte is a historic hill town in southern Italy’s Calabria region, known for its medieval architecture and scenic views over the surrounding countryside.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa7c9ec81908c685612994543e3 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62abfd9c081909803691d3fc4f149 |
completed | May 2, 2026, 4:48 p.m. |
Created at: April 8, 2026, 9:54 p.m.