Triple
T199742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Africa Time |
E4075
|
entity |
| Predicate | timeAheadOfUTC |
P4887
|
FINISHED |
| Object | 2 hours |
—
|
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: 2 hours | Statement: [Central Africa Time, timeAheadOfUTC, 2 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeAheadOfUTC Context triple: [Central Africa Time, timeAheadOfUTC, 2 hours]
-
A.
offsetInSecondsFromUTC
chosen
Indicates the time difference, measured in whole seconds, between a given time reference and Coordinated Universal Time (UTC).
-
B.
previousUTCOffset
Indicates the UTC time offset that applied to an entity (such as a timezone or location) immediately before the current or given offset.
-
C.
isOneHourAheadOf
Indicates that one entity’s local time is exactly one hour later than the other entity’s local time.
-
D.
UTCOffsetDaylightSavingTime
Indicates the time difference from Coordinated Universal Time (UTC) that applies to an entity specifically during daylight saving time periods.
-
E.
timeDifferenceToCETWinter
Indicates the time offset between a given time and Central European Time during the winter (standard time) period.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.