Triple
T26897129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Freeze |
E677924
|
entity |
| Predicate | durationInStory |
P10692
|
FINISHED |
| Object | several hours to a day (approximate, in-film time) |
—
|
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: several hours to a day (approximate, in-film time) | Statement: [Great Freeze, durationInStory, several hours to a day (approximate, in-film time)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: durationInStory Context triple: [Great Freeze, durationInStory, several hours to a day (approximate, in-film time)]
-
A.
storyTimeSpanInFilm
chosen
Indicates the duration of time that the story or narrative covers within the film.
-
B.
storyArcLength
Indicates the duration or extent of a narrative arc within a story, such as how long a particular plotline continues.
-
C.
timeOfNarrative
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
D.
intendedDuration
Indicates the planned or expected length of time for which an action, event, or state is meant to occur or remain in effect.
-
E.
narrativeTimeSpanHours
Indicates the duration of a narrative or story event measured in hours.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61fac4c808190a27f121fac4fe61c |
completed | May 2, 2026, 4 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:48 a.m.