Triple
T6518956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rossi |
E148330
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Mario Rossi
Mario Rossi is a common Italian placeholder name, similar to "John Smith" in English, often used to represent an unspecified or generic person.
|
E604994
|
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: Mario Rossi | Statement: [Rossi, hasNotableBearer, Mario Rossi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mario Rossi Context triple: [Rossi, hasNotableBearer, Mario Rossi]
-
A.
Leo Rossi
Leo Rossi is an American character actor known for his supporting roles in crime dramas and thrillers in film and television.
-
B.
Mario Girotti
Mario Girotti is the birth name of Italian actor Terence Hill, famed for his spaghetti westerns and action-comedy films, often alongside Bud Spencer.
-
C.
Furio Scarpelli
Furio Scarpelli was an influential Italian screenwriter renowned for co-writing numerous classics of Italian cinema, particularly in the commedia all’italiana genre.
-
D.
Enzo Rossi
Enzo Rossi is the son of American actress Patricia Arquette and musician Paul Rossi.
-
E.
Mario Tosi
Mario Tosi is an Italian-born cinematographer known for his work on several notable American films in the 1970s and 1980s.
- 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: Mario Rossi Triple: [Rossi, hasNotableBearer, Mario Rossi]
Generated description
Mario Rossi is a common Italian placeholder name, similar to "John Smith" in English, often used to represent an unspecified or generic person.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mario Rossi Target entity description: Mario Rossi is a common Italian placeholder name, similar to "John Smith" in English, often used to represent an unspecified or generic person.
-
A.
Leo Rossi
Leo Rossi is an American character actor known for his supporting roles in crime dramas and thrillers in film and television.
-
B.
Mario Girotti
Mario Girotti is the birth name of Italian actor Terence Hill, famed for his spaghetti westerns and action-comedy films, often alongside Bud Spencer.
-
C.
Furio Scarpelli
Furio Scarpelli was an influential Italian screenwriter renowned for co-writing numerous classics of Italian cinema, particularly in the commedia all’italiana genre.
-
D.
Enzo Rossi
Enzo Rossi is the son of American actress Patricia Arquette and musician Paul Rossi.
-
E.
Mario Tosi
Mario Tosi is an Italian-born cinematographer known for his work on several notable American films in the 1970s and 1980s.
- 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_69c687e68e748190baceb9298f32d3ed |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ac11d0e481908103c4b51de9521e |
completed | March 27, 2026, 4:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d51af5308190928c97ceb5d5fa2d |
completed | March 27, 2026, 7:06 p.m. |
| NEDg | Description generation | batch_69c6d6d9af148190ad9cd2cc31a70bb7 |
completed | March 27, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6d98506b88190aae3b4d887744648 |
completed | March 27, 2026, 7:24 p.m. |
Created at: March 27, 2026, 1:44 p.m.