Triple
T27868496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Einstein |
E704425
|
entity |
| Predicate | timeTravelExperimentDateInStory |
P164541
|
FINISHED |
| Object | October 26, 1985 |
—
|
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: October 26, 1985 | Statement: [Einstein, timeTravelExperimentDateInStory, October 26, 1985]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeTravelExperimentDateInStory Context triple: [Einstein, timeTravelExperimentDateInStory, October 26, 1985]
-
A.
timeTravelTo
Indicates traveling from one point in time to another, typically different, point in time.
-
B.
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.
-
C.
timeJump
Indicates a discontinuous transition of an entity from one point in time to another, skipping the intervening duration.
-
D.
timeTravelFrom
Indicates a relationship where an entity initiates time travel starting from a specific time or temporal location.
-
E.
timeTravelMethod
Indicates the specific mechanism or technique by which an entity performs or experiences time travel.
- F. None of above. chosen
Provenance (4 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_69f64e6e8c9081908ce4d364aa26147a |
completed | May 2, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f64db8ee1881909362701d72ffe282 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 27, 2026, 6:22 p.m.