Triple
T1638883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giovanni Ribisi |
E35421
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object |
Gay Ribisi
Gay Ribisi is the mother of American actor Giovanni Ribisi.
|
E189419
|
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: Gay Ribisi | Statement: [Giovanni Ribisi, mother, Gay Ribisi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gay Ribisi Context triple: [Giovanni Ribisi, mother, Gay Ribisi]
-
A.
Giovanni Ribisi
Giovanni Ribisi is an American actor known for his character roles in films like "Saving Private Ryan," "Avatar," and the TV series "Friends."
-
B.
John C. Reilly
John C. Reilly is an American actor known for his versatile performances in both dramatic films and broad comedies, including roles in movies like "Chicago," "Boogie Nights," and "Step Brothers."
-
C.
John Cusack
John Cusack is an American actor, screenwriter, and producer known for his roles in films like "Say Anything..." and "High Fidelity" and for his outspoken political activism.
-
D.
Michael Ealy
Michael Ealy is an American actor known for his roles in films like "Barbershop," "Think Like a Man," and "2 Fast 2 Furious," as well as various television series.
-
E.
Rob Lowe
Rob Lowe is an American actor known for his roles in films like "St. Elmo's Fire" and TV series such as "Parks and Recreation" and "9-1-1: Lone Star."
- 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: Gay Ribisi Triple: [Giovanni Ribisi, mother, Gay Ribisi]
Generated description
Gay Ribisi is the mother of American actor Giovanni Ribisi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gay Ribisi Target entity description: Gay Ribisi is the mother of American actor Giovanni Ribisi.
-
A.
Giovanni Ribisi
Giovanni Ribisi is an American actor known for his character roles in films like "Saving Private Ryan," "Avatar," and the TV series "Friends."
-
B.
John C. Reilly
John C. Reilly is an American actor known for his versatile performances in both dramatic films and broad comedies, including roles in movies like "Chicago," "Boogie Nights," and "Step Brothers."
-
C.
John Cusack
John Cusack is an American actor, screenwriter, and producer known for his roles in films like "Say Anything..." and "High Fidelity" and for his outspoken political activism.
-
D.
Michael Ealy
Michael Ealy is an American actor known for his roles in films like "Barbershop," "Think Like a Man," and "2 Fast 2 Furious," as well as various television series.
-
E.
Rob Lowe
Rob Lowe is an American actor known for his roles in films like "St. Elmo's Fire" and TV series such as "Parks and Recreation" and "9-1-1: Lone Star."
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a1c2b148190b6610237d5bede10 |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad71a61de8819095005c222ec50810 |
completed | March 8, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_69ad728cb27c8190802b30afc5e259e2 |
completed | March 8, 2026, 12:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad72fa21208190b596bfdfc69043bd |
completed | March 8, 2026, 1 p.m. |
Created at: March 4, 2026, 7:28 p.m.