Triple
T13446551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law & Order: LA |
E320498
|
entity |
| Predicate | typicalEpisodeRuntimeMinutes |
P11339
|
FINISHED |
| Object | 42 |
—
|
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: 42 | Statement: [Law & Order: LA, typicalEpisodeRuntimeMinutes, 42]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEpisodeRuntimeMinutes Context triple: [Law & Order: LA, typicalEpisodeRuntimeMinutes, 42]
-
A.
hasEpisodeRuntime
chosen
Indicates the duration of time that each individual episode of a series or show runs.
-
B.
typicalViewingTime
Indicates the usual or most common amount of time an entity is viewed or watched under normal circumstances.
-
C.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
D.
typicalSeasonSeriesLength
Indicates the usual number of episodes or installments that make up a single season of a series.
-
E.
hasEpisodeLengthType
Indicates the type or category of duration associated with an episode (e.g., standard length, short, extended).
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaef5f610819092cad33ef72075ff |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.