Triple
T34875418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UBS Evening News |
E1005867
|
entity |
| Predicate | timeSlotInFiction |
P181960
|
FINISHED |
| Object | prime time |
—
|
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: prime time | Statement: [UBS Evening News, timeSlotInFiction, prime time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSlotInFiction Context triple: [UBS Evening News, timeSlotInFiction, prime time]
-
A.
fictionalTime
Indicates that the associated time or temporal reference exists only within a fictional or imagined context, rather than in real-world chronology.
-
B.
associatedPeriodInFiction
Indicates a relationship where a fictional work, character, or event is linked to a specific time period within its fictional universe or narrative setting.
-
C.
fictionalTimeDepth
Indicates a relationship where an entity is associated with a time period or temporal depth that exists only within a fictional or imagined context.
-
D.
periodOfFictionalSetting
Indicates the time period in which the events of a fictional work are set.
-
E.
hasFictionalTimeAfter
Indicates that one fictional time point or period occurs later than another within a narrative or imagined timeline.
- 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_69f76dbde1c08190a24e7f9beb564c8d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f782f416c081908bdd9b1ad456f0e2 |
completed | May 3, 2026, 5:16 p.m. |
Created at: May 3, 2026, 4 p.m.