Triple
T36214568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Repeaters |
E1047652
|
entity |
| Predicate | hasTimeLoopNarrative |
P136389
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Repeaters, hasTimeLoopNarrative, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimeLoopNarrative Context triple: [Repeaters, hasTimeLoopNarrative, true]
-
A.
hasTemporalParadox
Indicates that a situation, event, or sequence of events involves a contradiction or inconsistency in time, such as conflicting timelines or causality loops.
-
B.
isTimeBendingStory
chosen
Indicates that a story involves manipulation, distortion, or non-linear progression of time as a central narrative element.
-
C.
narrativeCycle
Indicates a recurring or structured sequence of narrative events or themes that repeat or progress in a cyclical pattern within a story or across stories.
-
D.
hasFictionalTimeAfter
Indicates that one fictional time point or period occurs later than another within a narrative or imagined timeline.
-
E.
hasAlternateTimeline
Indicates that an entity exists or occurs in a different possible or parallel timeline relative to another reference timeline.
- 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_69f76e4214748190a76c986d2a1838c2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe066d62b48190867df334039be786 |
completed | May 8, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69fe03afde3c8190a5b9b0778d19eb1a |
completed | May 8, 2026, 3:39 p.m. |
Created at: May 3, 2026, 4:09 p.m.