Triple
T19056713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Berman |
E466414
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ted Berman |
—
|
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: Ted Berman | Statement: [Ted Berman, name, Ted Berman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Berman Context triple: [Ted Berman, name, Ted Berman]
-
A.
Ted Berman
chosen
Ted Berman was an American animator and film director best known for his work at Walt Disney Productions during the studio’s classic and transitional eras.
-
B.
Phillip Berman
Phillip Berman is a writer best known for coauthoring the spiritual and philosophical work "Reason for Hope: A Spiritual Journey" with primatologist Jane Goodall.
-
C.
Gregg Berger
Gregg Berger is an American voice actor known for his work in animation and video games, including roles in franchises like "Transformers" and various Spyro titles.
-
D.
Doug Berman
Doug Berman is an American radio producer best known for creating and producing popular NPR programs, including the news quiz show "Wait Wait... Don't Tell Me!" and the car-advice show "Car Talk."
-
E.
Glenn Berger
Glenn Berger is an American screenwriter best known for co-writing major animated films such as the Kung Fu Panda series.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc067f788190b3b149dfee370435 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 10, 2026, 12:03 p.m.