Triple
T37091438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (2045) |
E918429
|
entity |
| Predicate | hasFictionalSettingYear |
P197077
|
FINISHED |
| Object | 2045 |
—
|
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: 2045 | Statement: [SS Empress of Britain (2045), hasFictionalSettingYear, 2045]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSettingYear Context triple: [SS Empress of Britain (2045), hasFictionalSettingYear, 2045]
-
A.
hasFictionalSettingElement
Indicates that something includes or is associated with a specific element or component of a fictional setting.
-
B.
endsInFictionalYear
Indicates that an event, story, or timeline concludes in a year that exists only within a fictional or imagined setting.
-
C.
periodOfFictionalSetting
Indicates the time period in which the events of a fictional work are set.
-
D.
foundedInFictionalYear
Indicates that an entity was established or created in a year that exists only within a fictional or imaginary timeline, rather than in real-world history.
-
E.
yearOfFictionalEvent
chosen
Indicates the specific calendar year in which a fictional event is depicted as occurring within a narrative or fictional universe.
- 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_69f76e9a48bc8190a3947508d8bca408 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a0042524d8c8190884a10fce669ae95 |
completed | May 10, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_6a0041e89bd881909e32764699bcb89b |
completed | May 10, 2026, 8:29 a.m. |
Created at: May 3, 2026, 4:14 p.m.