Triple
T37777635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America/Sao_Paulo |
E941730
|
entity |
| Predicate | DSTEndYearInBrazil |
P189030
|
FINISHED |
| Object | 2019 |
—
|
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: 2019 | Statement: [America/Sao_Paulo, DSTEndYearInBrazil, 2019]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DSTEndYearInBrazil Context triple: [America/Sao_Paulo, DSTEndYearInBrazil, 2019]
-
A.
DSTEndRule
Indicates the rule or condition that specifies when daylight saving time ends in a given timekeeping system.
-
B.
typicalDSTEndMonth
Indicates the month in which daylight saving time typically ends for a given region or system.
-
C.
usesDSTEndInSouthernAutumn
Indicates that a region or entity observes daylight saving time that ends during the southern hemisphere’s autumn season.
-
D.
DSTseason
Indicates that the relationship specifies the daylight saving time (DST) period or season during which a time-related event or setting is in effect.
-
E.
DSTObservedBetweenYears
Indicates that daylight saving time was in effect at some point between the specified start and end years.
- 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_69f76ee4431881908f87e8892a9f39f3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbaf48ba148190a8bdfd6846ad0540 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbaeef9c488190babb546b962b4fb6 |
completed | May 6, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.