Triple
T13700904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La scuola cattolica |
E328513
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Stefano Mordini |
E1096195
|
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: Stefano Mordini | Statement: [La scuola cattolica, screenwriter, Stefano Mordini]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stefano Mordini Context triple: [La scuola cattolica, screenwriter, Stefano Mordini]
-
A.
Stefano Mordini
chosen
Stefano Mordini is an Italian film director and screenwriter known for his gritty, character-driven dramas.
-
B.
Stefano Pessina
Stefano Pessina is an Italian-Monegasque billionaire businessman best known as the longtime leader and major shareholder behind the global pharmacy and retail group Walgreens Boots Alliance.
-
C.
Stefano Dionisi
Stefano Dionisi is an Italian actor known for his work in both European cinema and international films.
-
D.
Filippo Barigioni
Filippo Barigioni was an Italian Baroque architect and sculptor active in Rome in the early 18th century, known for his work on churches, fountains, and urban spaces.
-
E.
Stefano Arnaldi
Stefano Arnaldi is a composer best known for creating the musical score for the film "Tea with Mussolini."
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc879adc88190b03f1cf815b71061 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c405ecc81909722377a22db84a5 |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 9, 2026, 9:54 p.m.