Triple
T16253955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Star Trek Online |
E394581
|
entity |
| Predicate | timelineSetting |
P89854
|
FINISHED |
| Object | 25th century |
—
|
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: 25th century | Statement: [Star Trek Online, timelineSetting, 25th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timelineSetting Context triple: [Star Trek Online, timelineSetting, 25th century]
-
A.
timelineUse
Indicates that one entity utilizes or incorporates another entity within a temporal sequence or schedule (a timeline).
-
B.
timeJump
Indicates a discontinuous transition of an entity from one point in time to another, skipping the intervening duration.
-
C.
chronologicalPoint
chosen
Indicates that something is associated with, occurs at, or is anchored to a specific point in time within a chronological sequence.
-
D.
timeShiftProperty
Indicates a relationship where one property value is derived from another by applying a temporal shift (e.g., offsetting it to an earlier or later point in time).
-
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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24598c9488190a92df7d8b1824724 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.