Triple
T2269797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nino Rota |
E50629
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Nino
Nino is the commonly used name of Italian composer Nino Rota, renowned for his film scores including those for Federico Fellini and The Godfather.
|
E251647
|
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: Nino | Statement: [Nino Rota, nickname, Nino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nino Context triple: [Nino Rota, nickname, Nino]
-
A.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
B.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
C.
Renzo
Renzo is the given name of Renzo Piano, the renowned Italian architect known for designing landmark buildings such as the Centre Pompidou in Paris and The Shard in London.
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Nico
Nico is a given name, typically a short form of Nicholas, used across various cultures for both males and females.
- 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: Nino Triple: [Nino Rota, nickname, Nino]
Generated description
Nino is the commonly used name of Italian composer Nino Rota, renowned for his film scores including those for Federico Fellini and The Godfather.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nino Target entity description: Nino is the commonly used name of Italian composer Nino Rota, renowned for his film scores including those for Federico Fellini and The Godfather.
-
A.
Nina
Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
-
B.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
C.
Renzo
Renzo is the given name of Renzo Piano, the renowned Italian architect known for designing landmark buildings such as the Centre Pompidou in Paris and The Shard in London.
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Nico
Nico is a given name, typically a short form of Nicholas, used across various cultures for both males and females.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1be90708190b8878c393dd2a42d |
completed | March 7, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71d97a108190a26ffd20fac91a7e |
completed | March 9, 2026, 7:08 a.m. |
| NEDg | Description generation | batch_69ae73a4bdd08190bb9fff64ffdbeed6 |
completed | March 9, 2026, 7:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae776fdfb48190ae8731002c537458 |
completed | March 9, 2026, 7:32 a.m. |
Created at: March 4, 2026, 7:48 p.m.