Triple
T15469873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee Town |
E372130
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object | CollegeHumor |
E1158714
|
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: CollegeHumor | Statement: [Coffee Town, distributor, CollegeHumor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CollegeHumor Context triple: [Coffee Town, distributor, CollegeHumor]
-
A.
CollegeHumor
chosen
CollegeHumor is a comedy brand and production company best known for its online sketch videos, web series, and humorous digital content.
-
B.
College Humor
College Humor is a 1933 American musical comedy film directed by Mark Sandrich and starring Bing Crosby, set around the antics and romances of college life.
-
C.
Comedy.TV
Comedy.TV is an American digital multicast television network and streaming channel focused on stand-up comedy and comedic programming.
-
D.
COMEDS
COMEDS is NATO’s senior committee responsible for coordinating and advising on multinational military medical policy, support, and interoperability across the Alliance.
-
E.
MADtv
MADtv is an American sketch comedy television series known for its ensemble cast, pop culture parodies, and long run on the Fox network from the mid-1990s into the 2000s.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f6b49788190b270fdfe92646842 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3657972481909219bc040f674c02 |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:33 a.m.