Triple
T19520911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barnyard |
E488397
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Cam Clarke |
—
|
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: Cam Clarke | Statement: [Barnyard, voiceActor, Cam Clarke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cam Clarke Context triple: [Barnyard, voiceActor, Cam Clarke]
-
A.
Cam Clarke
chosen
Cam Clarke is an American voice actor known for his work in animation and video games, including prominent roles in series like Teenage Mutant Ninja Turtles and various Disney productions.
-
B.
Alan Baxter
Alan Baxter was an American character actor known for his roles in mid-20th-century film and television, often portraying tough or villainous figures.
-
C.
Ray Sidney
Ray Sidney is an American software engineer and early Google employee who later became known as a philanthropist and real estate investor.
-
D.
Michael Kane
Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
-
E.
Michael Kane
Michael Kane is a creator known for developing the character Stefen Djordjevic.
- 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.