Triple
T3012484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chatham Standard Time |
E82253
|
entity |
| Predicate | isUnusualOffset |
P44982
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chatham Standard Time, isUnusualOffset, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUnusualOffset Context triple: [Chatham Standard Time, isUnusualOffset, true]
-
A.
isOffsetFrom
Indicates that one entity’s position, value, or occurrence is displaced by a specified amount or direction relative to another entity.
-
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.
offsets
Indicates that one entity counterbalances, compensates for, or reduces the effect, value, or impact of another.
-
D.
hasHalfHourOffset
Indicates that one entity’s time zone differs from another’s by an offset that includes a 30-minute (half-hour) component.
-
E.
typicalOffsetRange
Indicates the usual or expected range of positional or temporal deviation between related elements.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a66c334819082d1d320c48eca1b |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad961a97188190809dc73430a8eda8 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97ba55dc8190b6dddddfb751cf64 |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 8, 2026, 3 p.m.