Triple
T25706099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Five Get into Trouble |
E644591
|
entity |
| Predicate | recurringSeriesElements |
P58011
|
FINISHED |
| Object | rural and semi-rural settings |
—
|
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: rural and semi-rural settings | Statement: [Five Get into Trouble, recurringSeriesElements, rural and semi-rural settings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringSeriesElements Context triple: [Five Get into Trouble, recurringSeriesElements, rural and semi-rural settings]
-
A.
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.
-
B.
recurringSeriesSettingFor
Indicates that something serves as the setting or context in which a recurring series regularly takes place.
-
C.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
-
D.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
E.
recurringSegmentOn
chosen
Indicates that one entity appears repeatedly as a regular segment or feature within another entity, such as a show, publication, or series.
- 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 21, 2026, 9:05 p.m.