Triple
T4464948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangwon Province, North Korea |
E98353
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Wonsan |
E373041
|
NE 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: Wonsan | Statement: [Gangwon Province, North Korea, contains, Wonsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wonsan Context triple: [Gangwon Province, North Korea, contains, Wonsan]
-
A.
Wonsan
chosen
Wonsan is a port city on North Korea’s east coast, known for its strategic military importance and role as a regional transportation and industrial hub.
-
B.
Sinuiju, Korea
Sinuiju, Korea is a North Korean city on the Yalu River bordering China, known as an important industrial and transportation hub.
-
C.
Kim Chaek City
Kim Chaek City is an industrial port city in North Hamgyong Province, North Korea, named in honor of the Korean War general and politician Kim Chaek.
-
D.
Pyongyang
Pyongyang is the capital and largest city of North Korea, serving as its political, economic, and cultural center.
-
E.
Dangjin
Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b35697937c8190b91f72d9e4f945f6 |
completed | March 13, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6376c8e74819087aa2ff3e4429674 |
completed | March 15, 2026, 4:37 a.m. |
Created at: March 12, 2026, 11:34 p.m.