Triple
T20388211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beef |
E498012
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Jake Schreier |
—
|
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: Jake Schreier | Statement: [Beef, executiveProducer, Jake Schreier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake Schreier Context triple: [Beef, executiveProducer, Jake Schreier]
-
A.
Jake Schreier
chosen
Jake Schreier is an American film and music video director known for movies such as "Paper Towns" and "Robot & Frank."
-
B.
Josh Schaeffer
Josh Schaeffer is a film editor known for his work on major studio features, including the monster crossover blockbuster "Godzilla vs. Kong."
-
C.
Kyle Scheible
Kyle Scheible is the aloof, rebellious musician and love interest in the coming-of-age film "Lady Bird."
-
D.
Jason Gesser
Jason Gesser is a former American football quarterback best known for his standout college career at Washington State University and subsequent roles as a coach and sports analyst.
-
E.
Aaron Burckhard
Aaron Burckhard is an American drummer best known as one of the earliest drummers for the grunge band Nirvana during its formative years.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790d9e5881908bde7da9e5e541a0 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.