Triple
T12311552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paolina Leopardi |
E293489
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Paolina |
E675819
|
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: Paolina | Statement: [Paolina Leopardi, hasGivenName, Paolina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paolina Context triple: [Paolina Leopardi, hasGivenName, Paolina]
-
A.
Paolina
chosen
Paolina is a feminine given name, commonly used in Italian and other European languages, that is a variant of names like Paulina or Paula.
-
B.
Paola
Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
-
C.
Paola
Paola is a town in southeastern Malta known for its historic sites, including the prehistoric Ħal Saflieni Hypogeum and other cultural landmarks.
-
D.
Paola
Paola is a feminine given name of Latin origin commonly used in Spanish- and Italian-speaking countries.
-
E.
Massimiliana
Massimiliana is an Italian feminine given name, serving as the female counterpart of Massimiliano.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f02c0508190b10c0627cdaaba76 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e84fa708190854afc6afd425fd7 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:53 p.m.