Triple
T11524876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul–San Francisco |
E273265
|
entity |
| Predicate | timeZoneChange |
P99943
|
FINISHED |
| Object | crosses International Date Line |
—
|
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: crosses International Date Line | Statement: [Seoul–San Francisco, timeZoneChange, crosses International Date Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeZoneChange Context triple: [Seoul–San Francisco, timeZoneChange, crosses International Date Line]
-
A.
timeZoneFocus
Indicates that one entity is the primary time zone or temporal context being emphasized, referenced, or used as the main focus in relation to another entity.
-
B.
timeZoneDependence
Indicates how a process, value, or behavior changes or is determined based on the time zone in which it is considered.
-
C.
relatedTimeZone
Indicates that two entities are associated with or operate within the same or corresponding time zone(s).
-
D.
timeZoneContext
Indicates the time zone setting or context in which an event, action, or relationship is interpreted.
-
E.
DSTOffsetChange
Indicates a change in the time offset applied to a time zone due to the start or end of daylight saving time.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fd26648819083de19bcddf8ad69 |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822ef46988190a1c360da4ee14fef |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:37 p.m.