Triple
T38406177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapter One: MADMAX |
E901333
|
entity |
| Predicate | timeSettingRelativeToSeason1 |
P190916
|
FINISHED |
| Object | one year later |
—
|
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: one year later | Statement: [Chapter One: MADMAX, timeSettingRelativeToSeason1, one year later]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSettingRelativeToSeason1 Context triple: [Chapter One: MADMAX, timeSettingRelativeToSeason1, one year later]
-
A.
setDuringSeason
Indicates that an event, activity, or state occurs within or is associated with a specific season.
-
B.
timeOfYearPlayed
Indicates the specific time or season of the year during which an event or activity is performed or takes place.
-
C.
timeSettingVariant
Indicates a relationship where one time setting is an alternative or modified version of another time setting.
-
D.
typicalSeasonTiming
Indicates the usual time period or season during which something normally occurs or is expected to take place.
-
E.
originalSeasonStart
Indicates the date or point in time when a season (such as a sports league or TV series) first began or was originally launched.
- 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_69f76e61e79c81908b787d83b46ab92b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd34596288190b8e34a7a20b4c0db |
completed | May 7, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd31227708190a7df213597e66ca8 |
completed | May 7, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:31 p.m.