Triple
T19106275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luisa Mattioli |
E467662
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mattioli |
—
|
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: Mattioli | Statement: [Luisa Mattioli, familyName, Mattioli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mattioli Context triple: [Luisa Mattioli, familyName, Mattioli]
-
A.
Mattioli
chosen
Mattioli is an Italian surname historically associated with figures such as the 17th-century statesman Ercole Antonio Mattioli.
-
B.
Mazzantini
Mazzantini is an Italian surname most notably borne by the contemporary novelist and actress Margaret Mazzantini.
-
C.
Memmoli
Memmoli is an Italian-origin surname most notably associated with American character actor George Memmoli.
-
D.
Barelli
Barelli is an Italian surname associated with figures such as the 17th-century architect Agostino Barelli.
-
E.
Bressani
Bressani is an Italian surname most notably associated with the 17th-century Jesuit missionary and historian Giuseppe Bressani.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e37159688190a6896d9730214ba8 |
completed | April 20, 2026, 8:27 a.m. |
Created at: April 10, 2026, 12:04 p.m.