Triple
T17965705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Viterelli |
E449199
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Viterelli
Viterelli is an Italian surname most notably associated with Joe Viterelli, an American character actor known for his mobster roles in films like "Analyze This."
|
E1299417
|
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: Viterelli | Statement: [Joe Viterelli, familyName, Viterelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viterelli Context triple: [Joe Viterelli, familyName, Viterelli]
-
A.
Rutigliano
Rutigliano is a town and comune in the Apulia region of southern Italy, known for its agricultural traditions and historic architecture.
-
B.
Savelli
Savelli is an ancient Roman noble family that produced several prominent churchmen, including Pope Honorius IV.
-
C.
Piermarini
Piermarini is an Italian surname most notably associated with Giuseppe Piermarini, an 18th-century architect renowned for designing Milan’s Teatro alla Scala.
-
D.
Trevisani
Trevisani are the inhabitants or natives of the Italian city of Treviso, typically associated with its local culture and traditions.
-
E.
Lattanzi
Lattanzi is an Italian-origin surname borne by various notable individuals in fields such as entertainment and sports.
- 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: Viterelli Triple: [Joe Viterelli, familyName, Viterelli]
Generated description
Viterelli is an Italian surname most notably associated with Joe Viterelli, an American character actor known for his mobster roles in films like "Analyze This."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Viterelli Target entity description: Viterelli is an Italian surname most notably associated with Joe Viterelli, an American character actor known for his mobster roles in films like "Analyze This."
-
A.
Rutigliano
Rutigliano is a town and comune in the Apulia region of southern Italy, known for its agricultural traditions and historic architecture.
-
B.
Savelli
Savelli is an ancient Roman noble family that produced several prominent churchmen, including Pope Honorius IV.
-
C.
Piermarini
Piermarini is an Italian surname most notably associated with Giuseppe Piermarini, an 18th-century architect renowned for designing Milan’s Teatro alla Scala.
-
D.
Trevisani
Trevisani are the inhabitants or natives of the Italian city of Treviso, typically associated with its local culture and traditions.
-
E.
Lattanzi
Lattanzi is an Italian-origin surname borne by various notable individuals in fields such as entertainment and sports.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1380960819089a3c0dd7cd57e5e |
completed | April 19, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0330120d1881908801112f9f400cd0 |
completed | May 12, 2026, 1:50 p.m. |
| NEDg | Description generation | batch_6a0333edd0188190aa87c462813527a6 |
completed | May 12, 2026, 2:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03347520ac8190b0b1ebfa122bfbf0 |
completed | May 12, 2026, 2:08 p.m. |
Created at: April 10, 2026, 10:22 a.m.