Triple
T23868429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Same Time, Next Year |
E592652
|
entity |
| Predicate | recurringEventInPlot |
P16303
|
FINISHED |
| Object | annual rendezvous |
—
|
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: annual rendezvous | Statement: [Same Time, Next Year, recurringEventInPlot, annual rendezvous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringEventInPlot Context triple: [Same Time, Next Year, recurringEventInPlot, annual rendezvous]
-
A.
recurringEvent
chosen
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
-
B.
repeatedMotive
Indicates that the same motive recurs multiple times within a work, sequence, or context.
-
C.
recurringSeries
Indicates that an event, action, or pattern occurs repeatedly over time as part of an ongoing series rather than as a one-time instance.
-
D.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
E.
hasRecurringSeriesProtagonists
Indicates that a recurring series features one or more protagonists who appear repeatedly across its installments.
- 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cae643448190863c44df5f026482 |
completed | April 29, 2026, 9:09 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:14 p.m.