Triple
T413359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindu Kush |
E9537
|
entity |
| Predicate | timeZoneRegion |
P109
|
FINISHED |
| Object | UTC+4:30 (Afghanistan) vicinity |
—
|
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+4:30 (Afghanistan) vicinity | Statement: [Hindu Kush, timeZoneRegion, UTC+4:30 (Afghanistan) vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeZoneRegion Context triple: [Hindu Kush, timeZoneRegion, UTC+4:30 (Afghanistan) vicinity]
-
A.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
-
B.
relatedTimeZone
Indicates that two entities are associated with or operate within the same or corresponding time zone(s).
-
C.
capitalTimeZoneOf
Indicates that a specified time zone is the primary or official time zone in which a given capital city is located or operates.
-
D.
locatedInTimeZone
chosen
Indicates that an entity exists or an event occurs within the temporal bounds defined by a specific time zone.
-
E.
languageZone
Indicates the linguistic region or area in which a language is predominantly used or officially recognized.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecdc422881908910428fd1aee7c6 |
completed | Feb. 28, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69a2e9749234819084b0ce94faabd0b1 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.