Triple
T10368142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Santa |
E244308
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | John Cameron |
E349153
|
NE FINISHED |
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: John Cameron | Statement: [Bad Santa, producer, John Cameron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Cameron Context triple: [Bad Santa, producer, John Cameron]
-
A.
John Cameron
chosen
John Cameron is a British composer and arranger known for his work on film scores, television music, and popular recordings.
-
B.
Jack Cameron
Jack Cameron is an actor known for his role in the production "Applause."
-
C.
Ken Cameron
Ken Cameron is an Australian film director known for his work on adaptations of notable literary works, including the film version of "Monkey Grip."
-
D.
Ian Kirkpatrick
Ian Kirkpatrick is a Grammy-nominated American record producer and songwriter best known for crafting pop hits for artists like Dua Lipa, Selena Gomez, and Jason Derulo.
-
E.
Richard Ross
Richard Ross is a television producer and writer best known for co-creating the classic 1960s American sitcom "The Patty Duke Show."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e97106448190a075948e63184f47 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fb8e96e081908282bb0f82719abe |
completed | April 9, 2026, 7:18 p.m. |
Created at: April 6, 2026, 12:01 p.m.