Triple
T17855123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pier Luigi Bersani |
E445910
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Daniela Ferrari
Daniela Ferrari is known as the wife of Italian politician Pier Luigi Bersani, a prominent figure in Italy’s center-left politics.
|
E1304857
|
NE FINISHED |
How this triple was built (4 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: Daniela Ferrari | Statement: [Pier Luigi Bersani, spouse, Daniela Ferrari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniela Ferrari Context triple: [Pier Luigi Bersani, spouse, Daniela Ferrari]
-
A.
Daniela Farinacci
Daniela Farinacci is an Australian actress known for her work in film, television, and theatre, including a notable role in the acclaimed drama "Lantana."
-
B.
Daniela Bianchi
Daniela Bianchi is an Italian actress and former model best known for playing Bond girl Tatiana Romanova in the James Bond film "From Russia with Love" (1963).
-
C.
Daniela Nardini
Daniela Nardini is a Scottish actress best known for her BAFTA-winning role as Anna Forbes in the BBC drama series "This Life."
-
D.
Maria Ferrari
Maria Ferrari is known as the spouse of Australian film director Phillip Noyce.
-
E.
Giuliana Pozzo
Giuliana Pozzo is a member of the historically prominent Pozzo family, known for its influence and legacy in Italian cultural and social circles.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Daniela Ferrari Triple: [Pier Luigi Bersani, spouse, Daniela Ferrari]
Generated description
Daniela Ferrari is known as the wife of Italian politician Pier Luigi Bersani, a prominent figure in Italy’s center-left politics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daniela Ferrari Target entity description: Daniela Ferrari is known as the wife of Italian politician Pier Luigi Bersani, a prominent figure in Italy’s center-left politics.
-
A.
Daniela Farinacci
Daniela Farinacci is an Australian actress known for her work in film, television, and theatre, including a notable role in the acclaimed drama "Lantana."
-
B.
Daniela Bianchi
Daniela Bianchi is an Italian actress and former model best known for playing Bond girl Tatiana Romanova in the James Bond film "From Russia with Love" (1963).
-
C.
Daniela Nardini
Daniela Nardini is a Scottish actress best known for her BAFTA-winning role as Anna Forbes in the BBC drama series "This Life."
-
D.
Maria Ferrari
Maria Ferrari is known as the spouse of Australian film director Phillip Noyce.
-
E.
Giuliana Pozzo
Giuliana Pozzo is a member of the historically prominent Pozzo family, known for its influence and legacy in Italian cultural and social circles.
- F. None of above. chosen
Provenance (5 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4978af9b0819091780281344f5352 |
completed | April 19, 2026, 8:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a035d76eb3c81908d7b7a770a47f725 |
completed | May 12, 2026, 5:03 p.m. |
| NEDg | Description generation | batch_6a03633013148190b597d2ee923131d9 |
completed | May 12, 2026, 5:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0363b88210819098837b6e08083ac0 |
completed | May 12, 2026, 5:30 p.m. |
Created at: April 10, 2026, 10:17 a.m.