Triple
T27091000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America’s Funniest People |
E686166
|
entity |
| Predicate | isCompanionSeriesOf |
P133719
|
FINISHED |
| Object | America’s Funniest Home Videos |
—
|
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: America’s Funniest Home Videos | Statement: [America’s Funniest People, isCompanionSeriesOf, America’s Funniest Home Videos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCompanionSeriesOf Context triple: [America’s Funniest People, isCompanionSeriesOf, America’s Funniest Home Videos]
-
A.
hasSeriesCompanions
chosen
Indicates that one entity is accompanied by or associated with other entities as companions within the same series.
-
B.
worksInSeriesWith
Indicates that one entity collaborates or participates together with another entity within the same series or serialized work.
-
C.
formerSeries
Indicates that one entity was previously a series associated with another entity, but no longer holds that status.
-
D.
hasAssociatedTVSeries
Indicates that one entity is linked to another entity that is a related or derived television series.
-
E.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
- F. None of above.
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_69ef148940ec819097b5c20fbfbf7c81 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641dc8ff48190ab575d855616580c |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 8:40 a.m.