Triple
T22454130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brian Robbins |
E555068
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | AwesomenessTV |
—
|
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: AwesomenessTV | Statement: [Brian Robbins, notableWork, AwesomenessTV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AwesomenessTV Context triple: [Brian Robbins, notableWork, AwesomenessTV]
-
A.
AwesomenessTV
chosen
AwesomenessTV is a digital media and entertainment company known for producing youth-oriented online content, films, and television series.
-
B.
Bounce TV
Bounce TV is an American digital multicast television network primarily targeting African American audiences with a mix of movies, original series, and syndicated programming.
-
C.
Awesomeness Films
Awesomeness Films is a film production company known for creating youth-oriented movies and digital content, including adaptations of popular young adult novels.
-
D.
IGN TV
IGN TV is a video-focused arm of IGN that produces and hosts entertainment and gaming-related shows, reviews, and original video content.
-
E.
Viceland
Viceland was a cable television channel owned by Vice Media that focused on edgy, youth-oriented documentary and lifestyle programming.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4e2bd4819083e5bed44e9776c6 |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 16, 2026, 8:48 p.m.