Triple
T19127303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paola Levi-Montalcini |
E468218
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Paola |
—
|
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: Paola | Statement: [Paola Levi-Montalcini, givenName, Paola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paola Context triple: [Paola Levi-Montalcini, givenName, Paola]
-
A.
Paola
Paola is a town in southeastern Malta known for its historic sites, including the prehistoric Ħal Saflieni Hypogeum and other cultural landmarks.
-
B.
Paola
Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
-
C.
Paola
chosen
Paola is a feminine given name of Latin origin commonly used in Spanish- and Italian-speaking countries.
-
D.
Giovannina
Giovannina is an Italian feminine given name, typically used as a diminutive or affectionate form of Giovanna.
-
E.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3cd851081909d5665b362ae08de |
completed | April 20, 2026, 8:29 a.m. |
Created at: April 10, 2026, 12:05 p.m.