Triple
T22630639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KST |
E558538
|
entity |
| Predicate | category |
P87
|
FINISHED |
| Object | Time in South Korea |
—
|
NE NERFINISHED |
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: Time in South Korea | Statement: [KST, category, Time in South Korea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Time in South Korea Context triple: [KST, category, Time in South Korea]
-
A.
Pyongyang Time
Pyongyang Time is the official standard time used in North Korea’s capital, Pyongyang, and throughout the country.
-
B.
Korea Standard Time
chosen
Korea Standard Time is the time zone used on the Korean Peninsula, set at UTC+9 hours.
-
C.
Daegu, South Korea
Daegu, South Korea is a major city in the southeastern part of the country known for its role as an industrial, cultural, and educational center.
-
D.
Osan, South Korea
Osan is a city in Gyeonggi Province, South Korea, known for its proximity to Osan Air Base and its role as a transportation and commercial hub south of Seoul.
-
E.
Daejeon, South Korea
Daejeon, South Korea is a major inland city known as a national hub for science, technology, and research, home to numerous universities, government research institutes, and high-tech industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17008e7648190b243c18067b4efb9 |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:02 p.m.