Triple
T8502029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outstanding Variety Sketch Series |
E201239
|
entity |
| Predicate | typicalRuntimeOfEligiblePrograms |
P74363
|
FINISHED |
| Object | half-hour series |
—
|
LITERAL 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: half-hour series | Statement: [Outstanding Variety Sketch Series, typicalRuntimeOfEligiblePrograms, half-hour series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRuntimeOfEligiblePrograms Context triple: [Outstanding Variety Sketch Series, typicalRuntimeOfEligiblePrograms, half-hour series]
-
A.
typicalRuntimeRange
Indicates the usual lower and upper bounds of time typically required for an entity to run or complete its operation.
-
B.
typicalRuntimePerShort
Indicates the usual or average amount of time it takes to complete a short instance of the referenced activity or process.
-
C.
hasRunningTimeCategory
chosen
Indicates that an entity is associated with a specific category based on its running time or duration.
-
D.
typicalBroadcastPeriod
Indicates the usual or standard time interval during which something is broadcast or transmitted.
-
E.
programLength
Indicates the duration or total length of a program, typically measured in time or size.
- 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe59ad65c8190a2b8e6d22269853a |
completed | March 31, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cbd10a4b0881909e254117780dc823 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:14 p.m.