Triple
T17863070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Burnham |
E446121
|
entity |
| Predicate | timeTravelInvolvement |
P129055
|
FINISHED |
| Object | Traveled to the 32nd century with USS Discovery |
—
|
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: Traveled to the 32nd century with USS Discovery | Statement: [Michael Burnham, timeTravelInvolvement, Traveled to the 32nd century with USS Discovery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeTravelInvolvement Context triple: [Michael Burnham, timeTravelInvolvement, Traveled to the 32nd century with USS Discovery]
-
A.
timeTravelType
Indicates the specific method or mechanism by which time travel is carried out in a given context.
-
B.
timeTravelPurpose
Indicates that an instance of time travel is undertaken with a specific goal, motive, or intended outcome in mind.
-
C.
timeTravelDeviceUsed
Indicates that an entity makes use of a device or mechanism that enables travel through 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.
timeTravelTrigger
Indicates an event, condition, or mechanism that initiates or enables time travel to occur.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e49791b0c08190b04a426bd274065d |
completed | April 19, 2026, 8:51 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:17 a.m.