Triple
T27868495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Einstein |
E704425
|
entity |
| Predicate | timeMachineUsed |
P79914
|
FINISHED |
| Object | DeLorean time machine |
—
|
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: DeLorean time machine | Statement: [Einstein, timeMachineUsed, DeLorean time machine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeMachineUsed Context triple: [Einstein, timeMachineUsed, DeLorean time machine]
-
A.
timeMachineSpeedRequirement
Indicates the minimum speed or velocity that must be reached or maintained for a time machine to successfully enable time travel.
-
B.
timeTravelDeviceUsed
chosen
Indicates that an entity makes use of a device or mechanism that enables travel through time.
-
C.
isTimeCapsule
Indicates that something functions as a time capsule, preserving items or information to be opened or accessed at a later, specified time.
-
D.
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.
-
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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6394a0a908190b88187af34f8f20c |
completed | May 2, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69f6318be69481909d1bcf29b7b60eb2 |
completed | May 2, 2026, 5:17 p.m. |
Created at: April 27, 2026, 6:22 p.m.