Triple
T29549053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Sam Beckett |
E749710
|
entity |
| Predicate | methodOfTimeTravel |
P22749
|
FINISHED |
| Object | Project Quantum Leap accelerator |
—
|
NE NERFINISHED |
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: Project Quantum Leap accelerator | Statement: [Dr. Sam Beckett, methodOfTimeTravel, Project Quantum Leap accelerator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: methodOfTimeTravel Context triple: [Dr. Sam Beckett, methodOfTimeTravel, Project Quantum Leap accelerator]
-
A.
timeTravelMethod
chosen
Indicates the specific mechanism or technique by which an entity performs or experiences time travel.
-
B.
timeTravelTo
Indicates traveling from one point in time to another, typically different, point in time.
-
C.
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.
-
D.
timeTravelType
Indicates the specific method or mechanism by which time travel is carried out in a given context.
-
E.
timeTravelElement
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_69f0bd48691081908cecad39bac591e0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 28, 2026, 5:10 p.m.