Triple
T13581182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodbye Christopher Robin |
E324419
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | DJ Films |
E977921
|
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: DJ Films | Statement: [Goodbye Christopher Robin, productionCompany, DJ Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJ Films Context triple: [Goodbye Christopher Robin, productionCompany, DJ Films]
-
A.
DJ Films
chosen
DJ Films is a British film production company known for developing and producing feature films, including the 2016 adaptation of "Dad's Army."
-
B.
Sketch Films
Sketch Films is a television production company best known for its work on the supernatural drama series "Sleepy Hollow."
-
C.
CNN Films
CNN Films is a documentary film division of CNN that produces and acquires non-fiction feature films for theatrical release and television broadcast.
-
D.
Dohafilms
Dohafilms is a film production company known for helping produce the 2014 animated adaptation of Kahlil Gibran’s "The Prophet."
-
E.
MDB Films
MDB Films is a film production company known for producing the movie "The Kingdom."
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb031e8048190a5f2ea934308036c |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bbf946c8190ba3d2b87cb11dc9d |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.