Triple
T15904893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcello Mastroianni |
E385685
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Flora Carabella
Flora Carabella was an Italian actress best known for her work in mid-20th-century Italian cinema and theatre.
|
E1183521
|
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: Flora Carabella | Statement: [Marcello Mastroianni, spouse, Flora Carabella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flora Carabella Context triple: [Marcello Mastroianni, spouse, Flora Carabella]
-
A.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
B.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
-
C.
Rosana
Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
-
D.
Viviana
Viviana is a central protagonist in the television sitcom "Love, Inc.," around whom much of the show's matchmaking and personal drama revolves.
-
E.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
- 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: Flora Carabella Triple: [Marcello Mastroianni, spouse, Flora Carabella]
Generated description
Flora Carabella was an Italian actress best known for her work in mid-20th-century Italian cinema and theatre.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Flora Carabella Target entity description: Flora Carabella was an Italian actress best known for her work in mid-20th-century Italian cinema and theatre.
-
A.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
B.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
-
C.
Rosana
Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
-
D.
Viviana
Viviana is a central protagonist in the television sitcom "Love, Inc.," around whom much of the show's matchmaking and personal drama revolves.
-
E.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1565956588190ba4726a2879b677d |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb051a05081908c349cd9a1ff247a |
completed | May 9, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_69ffb1742e2c8190ab7fd714a8f38312 |
completed | May 9, 2026, 10:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb1eedaf481908d70e3517fbd5492 |
completed | May 9, 2026, 10:15 p.m. |
Created at: April 10, 2026, 4:52 a.m.