Triple
T16612031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosie |
E403597
|
entity |
| Predicate | televisionSeriesRuntimeCharacteristic |
P123539
|
FINISHED |
| Object | short-lived 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: short-lived series | Statement: [Rosie, televisionSeriesRuntimeCharacteristic, short-lived series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: televisionSeriesRuntimeCharacteristic Context triple: [Rosie, televisionSeriesRuntimeCharacteristic, short-lived series]
-
A.
hasEpisodeRuntime
Indicates the duration of time that each individual episode of a series or show runs.
-
B.
runningTimeMiniSeriesVersion
Indicates the duration of the mini-series version of a work, typically measured in time units such as minutes.
-
C.
typicalViewingTime
Indicates the usual or most common amount of time an entity is viewed or watched under normal circumstances.
-
D.
filmRuntimeApprox
Indicates an approximate or estimated duration of a film, rather than its exact runtime.
-
E.
filmRuntimeMinutes
Indicates the duration of a film expressed in minutes.
- F. None of above. chosen
Provenance (4 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36096356c819092815d64db041793 |
completed | April 18, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:17 a.m.