Triple
T14213737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Future Man |
E352293
|
entity |
| Predicate | hasTimeTravel |
P51702
|
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: [Future Man, hasTimeTravel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimeTravel Context triple: [Future Man, hasTimeTravel, 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.
timeTravelMethod
Indicates the specific mechanism or technique by which an entity performs or experiences time travel.
-
D.
timeTravelTo
Indicates traveling from one point in time to another, typically different, point in time.
-
E.
timeTravelElement
chosen
Indicates that the situation, event, or narrative involves an element of time travel, such as moving between different points in time or altering temporal sequences.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de620f07bc81909212dcd1c91b5f95 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:06 a.m.