Triple
T21940643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acre Time |
E541809
|
entity |
| Predicate | offsetFromBrasiliaTime |
P128549
|
FINISHED |
| Object | −02:00 |
—
|
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: −02:00 | Statement: [Acre Time, offsetFromBrasiliaTime, −02:00]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offsetFromBrasiliaTime Context triple: [Acre Time, offsetFromBrasiliaTime, −02:00]
-
A.
relativeOffsetToBrasiliaTime
chosen
Indicates the time difference or offset between a given time reference and Brasília’s local time.
-
B.
offsetFromBeijingTime
Indicates the time difference between a given time reference and Beijing time, typically expressed as an offset in hours or minutes.
-
C.
offsetFromUTC
Indicates the time difference between a given time value and Coordinated Universal Time (UTC), typically expressed as an offset in hours and/or minutes.
-
D.
offsetFromJapanStandardTime
Indicates the time difference between a given time zone or time value and Japan Standard Time (JST), typically expressed as an offset in hours or minutes.
-
E.
offsetFromBombayTime
Indicates the time difference between a given time reference and the local time in Bombay (Mumbai), typically expressed as an offset in hours or minutes.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12420b1cc81909b375891aedc0979 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:55 p.m.