Triple
T17908915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Arms |
E447770
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Eric Bauza |
—
|
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: Eric Bauza | Statement: [Four Arms, voiceActor, Eric Bauza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Bauza Context triple: [Four Arms, voiceActor, Eric Bauza]
-
A.
Eric Bauza
chosen
Eric Bauza is a Canadian voice actor and comedian best known for portraying iconic animated characters in modern Looney Tunes productions.
-
B.
Josh Brener
Josh Brener is an American actor best known for his comedic roles in television series like "Silicon Valley" and films such as "The Internship."
-
C.
Chris DiDomenico
Chris DiDomenico is a Canadian professional ice hockey forward known for his playmaking skills and for having played in both the NHL and various European leagues.
-
D.
Joel Murray
Joel Murray is an American actor and comedian known for his character roles in film and television, as well as for his voice work in animated projects.
-
E.
Matt Barr
Matt Barr is an American actor known for his roles in television series such as "Hatfields & McCoys," "One Tree Hill," and "Valor."
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9e4c9881908bfc3a83809d6b85 |
completed | April 19, 2026, 9:21 a.m. |
Created at: April 10, 2026, 10:19 a.m.