Triple
T8494202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City |
E201052
|
entity |
| Predicate | timeSpanOfStories |
P11197
|
FINISHED |
| Object | thousands of years into the future |
—
|
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: thousands of years into the future | Statement: [City, timeSpanOfStories, thousands of years into the future]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSpanOfStories Context triple: [City, timeSpanOfStories, thousands of years into the future]
-
A.
narrativeTimeSpanHours
Indicates the duration of a narrative or story event measured in hours.
-
B.
numberOfStories
Indicates the total count of levels or floors that a structure or building has.
-
C.
timeOfNarrative
chosen
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
D.
storyTimeSpanInFilm
Indicates the duration of time that the story or narrative covers within the film.
-
E.
collectionTimespan
Indicates the time period over which a collection exists, is accumulated, or is considered valid.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe57c01f881908cb77c8c834ac08d |
completed | March 31, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cbd10a4b0881909e254117780dc823 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:13 p.m.