Triple
T20375438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donny & Marie |
E497678
|
entity |
| Predicate | typicalShowLength |
P18065
|
FINISHED |
| Object | about 90 minutes |
—
|
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: about 90 minutes | Statement: [Donny & Marie, typicalShowLength, about 90 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalShowLength Context triple: [Donny & Marie, typicalShowLength, about 90 minutes]
-
A.
typicalViewingTime
Indicates the usual or most common amount of time an entity is viewed or watched under normal circumstances.
-
B.
typicalSeasonSeriesLength
Indicates the usual number of episodes or installments that make up a single season of a series.
-
C.
televisionSeriesRuntimeCharacteristic
Indicates a relationship where a television series is associated with a specific runtime-related characteristic, such as typical episode length or overall duration pattern.
-
D.
hasEpisodeLengthType
Indicates the type or category of duration associated with an episode (e.g., standard length, short, extended).
-
E.
typicalLength
chosen
Indicates the usual or characteristic length associated with an entity or phenomenon.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678acae3c8190ae04323760bf5597 |
completed | April 20, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:27 a.m.