Triple
T4459205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anadyr Time |
E98209
|
entity |
| Predicate | isPartOfTimeZoneSystem |
P44993
|
FINISHED |
| Object | Russian time zones |
—
|
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: Russian time zones | Statement: [Anadyr Time, isPartOfTimeZoneSystem, Russian time zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfTimeZoneSystem Context triple: [Anadyr Time, isPartOfTimeZoneSystem, Russian time zones]
-
A.
partOfTimeZone
Indicates that one time-related entity (such as a time, date-time, or region) belongs to or falls within a specific time zone.
-
B.
hasTimeZones
Indicates that an entity is associated with one or more time zones in which it is valid or operates.
-
C.
isSubnationalTimeZoneOf
chosen
Indicates that a time zone is officially used within, and is a subdivision-specific part of, a particular country or larger political entity.
-
D.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
-
E.
hasNumberOfNationalTimeZones
Indicates the quantity of distinct official time zones that a nation or country uses within its territory.
- 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_69b3454a7c608190944f5455c8031d73 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3567184f481908a2787e4ac9bb345 |
completed | March 13, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69b34f649df081909d3cc2f6a1b8f282 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:33 p.m.