Triple
T17680882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Time |
E440764
|
entity |
| Predicate | hasOffsetType |
P25007
|
FINISHED |
| Object | UTC−04:00 fixed offset |
—
|
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: UTC−04:00 fixed offset | Statement: [Amazon Time, hasOffsetType, UTC−04:00 fixed offset]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOffsetType Context triple: [Amazon Time, hasOffsetType, UTC−04:00 fixed offset]
-
A.
offsetType
chosen
Indicates the specific kind or category of offset applied in a relationship, such as how far or in what manner one value, position, or event is shifted relative to another.
-
B.
isOffsetFrom
Indicates that one entity’s position, value, or occurrence is displaced by a specified amount or direction relative to another entity.
-
C.
hasOffsetNullPins
Indicates that one entity has pins that are offset from a reference position and intentionally left unconnected or null.
-
D.
hasTimeOffset
Indicates that one temporal value is shifted or displaced from another by a specified amount of time.
-
E.
isUnusualOffset
Indicates that one value or position deviates from the expected or standard offset relative to another.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e470445b3881908bb0930b986089f7 |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:01 a.m.