Triple
T21379695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giovanni Lilliu |
E527311
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Giovanni Lilliu |
—
|
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: Giovanni Lilliu | Statement: [Giovanni Lilliu, name, Giovanni Lilliu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Giovanni Lilliu Context triple: [Giovanni Lilliu, name, Giovanni Lilliu]
-
A.
Giovanni Lilliu
chosen
Giovanni Lilliu was a prominent Italian archaeologist and scholar renowned for his pioneering studies of Nuragic civilization in Sardinia.
-
B.
Paolo Mastropietro
Paolo Mastropietro is an Italian-born actor and restaurateur best known as the husband of Canadian actress and singer Jill Hennessy.
-
C.
Sandro Petraglia
Sandro Petraglia is an Italian screenwriter best known for his work on acclaimed films and television series that explore contemporary Italian history and society.
-
D.
Stefano Arnaldi
Stefano Arnaldi is a composer best known for creating the musical score for the film "Tea with Mussolini."
-
E.
Gianni Alemanno
Gianni Alemanno is an Italian right-wing politician best known for serving as Mayor of Rome from 2008 to 2013.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0cc2b5c8190aa5f20f920523fe9 |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:11 p.m.