Triple
T21956712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avatar 3 |
E542206
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Giovanni Ribisi |
—
|
NE NERFINISHED |
How this triple was built (2 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: Giovanni Ribisi | Statement: [Avatar 3, stars, Giovanni Ribisi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Giovanni Ribisi Context triple: [Avatar 3, stars, Giovanni Ribisi]
-
A.
Giovanni Ribisi
chosen
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 Magaro
John Magaro is an American actor known for his work in film, television, and theater, including notable roles in projects like "The Big Short," "First Cow," and various Broadway productions.
-
C.
Michael Bell
Michael Bell is an American voice actor known for his extensive work in animated television series, films, and video games since the 1970s.
-
D.
Aaron Eckhart
Aaron Eckhart is an American actor best known for his roles in films such as "The Dark Knight," "Thank You for Smoking," and "Erin Brockovich."
-
E.
Matthew Daddario
Matthew Daddario is an American actor best known for his role as Alec Lightwood on the television series "Shadowhunters."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124404f38819080bae736a52a51cd |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:59 p.m.