Triple
T21360396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flaminio Bertoni |
E526759
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Flaminio |
—
|
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: Flaminio | Statement: [Flaminio Bertoni, givenName, Flaminio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flaminio Context triple: [Flaminio Bertoni, givenName, Flaminio]
-
A.
Flaminio
Flaminio is a central district of Rome known for its cultural institutions, modern architecture, and proximity to the Tiber River and major city landmarks.
-
B.
Marcello Romolo
Marcello Romolo is an actor known for his role in the television series "The Young Pope."
-
C.
Flaminio Ponzio
chosen
Flaminio Ponzio was an Italian architect of the late Renaissance and early Baroque period, known for his work in Rome under Pope Paul V.
-
D.
Mazzano Romano
Mazzano Romano is a small historic town in the Lazio region of central Italy, known for its medieval architecture and scenic location in the countryside north of Rome.
-
E.
Lucio
Lucio is a popular support hero in the game Overwatch, known for his music-based abilities that heal and speed up teammates.
- 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8afa6afcc8190a1f5c599c11d2135 |
completed | April 22, 2026, 11:23 a.m. |
Created at: April 16, 2026, 5:08 p.m.