Triple
T22472052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brahm Wenger |
E555525
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Snow Buddies |
—
|
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: Snow Buddies | Statement: [Brahm Wenger, notableWork, Snow Buddies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snow Buddies Context triple: [Brahm Wenger, notableWork, Snow Buddies]
-
A.
Snow Buddies
chosen
Snow Buddies is a family-friendly Disney direct-to-video film in the Air Buddies franchise that follows a group of talking golden retriever puppies on a snowy Alaskan adventure.
-
B.
Snow Wonder
Snow Wonder is a 2005 made-for-television holiday drama film that intertwines multiple characters' lives during a Christmas Eve snowstorm.
-
C.
Snowlets
Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
-
D.
Santa Buddies
Santa Buddies is a 2009 direct-to-video family Christmas film in the Air Buddies franchise, featuring talking golden retriever puppies who help save Christmas.
-
E.
Snowman
Snowman is the post-apocalyptic survivor and narrator of Margaret Atwood’s dystopian novel "Oryx and Crake," through whose perspective the story’s ruined world and its origins are revealed.
- 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15be0d3c08190851537660cda619c |
completed | April 29, 2026, 1:16 a.m. |
Created at: April 16, 2026, 8:48 p.m.