Triple
T3779920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Passions |
E85391
|
entity |
| Predicate | originalRunTimeSlot |
P14564
|
FINISHED |
| Object | weekday daytime |
—
|
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: weekday daytime | Statement: [Passions, originalRunTimeSlot, weekday daytime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalRunTimeSlot Context triple: [Passions, originalRunTimeSlot, weekday daytime]
-
A.
originalRuntime
Indicates the initial or primary duration associated with something, typically before any edits, changes, or adjustments are made.
-
B.
broadcastTimeSlot
chosen
Indicates the specific time period during which a broadcast (such as a TV or radio program) is scheduled to air.
-
C.
originalRunStatus
Indicates the initial or prior execution state of a run before any subsequent updates or changes.
-
D.
originalRunStartNetwork
Indicates the network on which a program or series first began its original broadcast run.
-
E.
typicalRuntimePerShort
Indicates the usual or average amount of time it takes to complete a short instance of the referenced activity or process.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
Created at: March 9, 2026, 3:12 p.m.