Triple
T29140758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Clitheroe Kid (radio appearances) |
E738624
|
entity |
| Predicate | regularOrRecurring |
P164570
|
FINISHED |
| Object | regular supporting role |
—
|
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: regular supporting role | Statement: [The Clitheroe Kid (radio appearances), regularOrRecurring, regular supporting role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regularOrRecurring Context triple: [The Clitheroe Kid (radio appearances), regularOrRecurring, regular supporting role]
-
A.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
B.
recurringActivity
chosen
Indicates that an activity or event occurs repeatedly over time according to some regular or defined pattern.
-
C.
meetsRegularly
Indicates that two or more entities come together on a recurring or scheduled basis.
-
D.
recurrenceType
Indicates the pattern or frequency with which an event or action repeats over time.
-
E.
regularCategory
Indicates that a category satisfies the additional structural conditions required to be considered a “regular” category, typically involving stable image factorizations and certain pullback properties.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: April 28, 2026, 11:36 a.m.