Triple
T4154246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America/Belize |
E89977
|
entity |
| Predicate | dstOffsetSameAsStandard |
P54667
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [America/Belize, dstOffsetSameAsStandard, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dstOffsetSameAsStandard Context triple: [America/Belize, dstOffsetSameAsStandard, yes]
-
A.
offsetStandardApprox
Indicates that one value serves as an approximate standard or baseline from which another value is offset or deviates.
-
B.
usesOffsetFrom
Indicates that one entity determines or expresses its position, value, or behavior relative to another by applying a specified offset from that reference.
-
C.
offsetDSTDifferenceHours
Indicates the difference in time zone offsets, measured in hours, that results specifically from the application of daylight saving time.
-
D.
isOffsetFrom
Indicates that one entity’s position, value, or occurrence is displaced by a specified amount or direction relative to another entity.
-
E.
offsetDSTApprox
Indicates an approximate time offset between entities that accounts for daylight saving time adjustments.
- 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_69aed95a59a881909b26e70b42c6811a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af033ef6648190adde17f943d89c78 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018c101081909070da5b11e5eb3d |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af033d94888190b34349e355b874ef |
completed | March 9, 2026, 5:28 p.m. |
Created at: March 9, 2026, 3:44 p.m.