Triple
T6248149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District Courts of South Korea |
E139772
|
entity |
| Predicate | hasSeatIn |
P3522
|
FINISHED |
| Object | Chuncheon |
E465846
|
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: Chuncheon | Statement: [District Courts of South Korea, hasSeatIn, Chuncheon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chuncheon Context triple: [District Courts of South Korea, hasSeatIn, Chuncheon]
-
A.
Chuncheon
chosen
Chuncheon is a city in northeastern South Korea known for its lakes, surrounding mountains, and status as the capital of Gangwon Province.
-
B.
Jecheon
Jecheon is a city in North Chungcheong Province, South Korea, known as a regional transport hub surrounded by mountains and lakes.
-
C.
Cheongju
Cheongju is a major city in central South Korea that serves as the capital of North Chungcheong Province and an important regional administrative, educational, and transportation hub.
-
D.
Jincheon
Jincheon is a county in North Chungcheong Province, South Korea, known for its agricultural production and growing role as a logistics and industrial hub.
-
E.
Icheon
Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633a9a048190856d5247d3b28a2e |
completed | March 22, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72f6514948190a5562201e7b36e27 |
completed | March 28, 2026, 1:31 a.m. |
Created at: March 22, 2026, 4:23 p.m.