Triple
T19520965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wild Thornberrys Movie |
E488398
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Tom Kane |
—
|
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: Tom Kane | Statement: [The Wild Thornberrys Movie, voiceActor, Tom Kane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Kane Context triple: [The Wild Thornberrys Movie, voiceActor, Tom Kane]
-
A.
Tom Kane
chosen
Tom Kane is an American voice actor best known for his extensive work in animation and video games, including roles in the Star Wars franchise.
-
B.
Nolan North
Nolan North is a prolific American voice actor best known for his performances in major video game franchises such as Uncharted, Assassin’s Creed, and Destiny.
-
C.
Mike Winchell
Mike Winchell is a high school quarterback character from "Friday Night Lights," known for his quiet leadership and pressure-filled role on the Permian Panthers football team.
-
D.
Eric Bauza
Eric Bauza is a Canadian voice actor and comedian best known for portraying iconic animated characters in modern Looney Tunes productions.
-
E.
Kal Penn
Kal Penn is an American actor and former White House staff member best known for his roles in the "Harold & Kumar" film series and the TV show "House."
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635a0b37c8190b70b7427c2e85f59 |
completed | April 20, 2026, 2:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.