Triple
T19901438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Barr |
E478299
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Matt Barr |
—
|
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: Matt Barr | Statement: [Matt Barr, name, Matt Barr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Barr Context triple: [Matt Barr, name, Matt Barr]
-
A.
Matt Barr
chosen
Matt Barr is an American actor known for his roles in television series such as "Hatfields & McCoys," "One Tree Hill," and "Valor."
-
B.
Matt Dabner
Matt Dabner is a film industry professional associated with the Australian production company Blue-Tongue Films, known for its work in independent cinema.
-
C.
Eric Bauza
Eric Bauza is a Canadian voice actor and comedian best known for portraying iconic animated characters in modern Looney Tunes productions.
-
D.
Kyle Dunnigan
Kyle Dunnigan is an American comedian, actor, and writer known for his sketch work, stand-up, and frequent collaborations with Amy Schumer.
-
E.
Jason Ritter
Jason Ritter is an American actor known for his work in film and television, including roles in series like "Parenthood" and "Joan of Arcadia."
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65941977081909e2f94724eb2c3c0 |
completed | April 20, 2026, 4:50 p.m. |
Created at: April 10, 2026, 1:52 p.m.