Triple
T2521085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Real World |
E55523
|
entity |
| Predicate | recurringElement |
P10543
|
FINISHED |
| Object | confessional interviews |
—
|
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: confessional interviews | Statement: [The Real World, recurringElement, confessional interviews]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringElement Context triple: [The Real World, recurringElement, confessional interviews]
-
A.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
-
B.
hasRecurringElement
chosen
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
C.
recurrence
Indicates that an event, condition, or state happens again or repeatedly over time, often after a period of absence or resolution.
-
D.
recurringLocation
Indicates that an event, action, or state happens repeatedly at the specified location over time.
-
E.
recurs
Indicates that an event, condition, or pattern happens again, often repeatedly or at regular intervals, after having occurred before.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2367b6c819094239dfd12399643 |
completed | March 7, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69abd0c144b0819092f32a13c1d127e5 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.