Triple
T29340090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Purple Tentacle |
E744012
|
entity |
| Predicate | hasTimeTravelInPlot |
P129055
|
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: [Purple Tentacle, hasTimeTravelInPlot, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimeTravelInPlot Context triple: [Purple Tentacle, hasTimeTravelInPlot, true]
-
A.
usesTimeTravelFor
Indicates a relationship where an entity employs time travel as a means or method to achieve, affect, or interact with another entity or objective.
-
B.
hasTemporalParadox
Indicates that a situation, event, or sequence of events involves a contradiction or inconsistency in time, such as conflicting timelines or causality loops.
-
C.
timeTravelInvolvement
chosen
Indicates that an entity participates in, is affected by, or is otherwise involved in an instance of time travel.
-
D.
hasFictionalTimeAfter
Indicates that one fictional time point or period occurs later than another within a narrative or imagined timeline.
-
E.
timeTravelType
Indicates the specific method or mechanism by which time travel is carried out in a given context.
- 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 28, 2026, 1:33 p.m.