Triple
T2929838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagano |
E78933
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Taejon (Daejeon), South Korea |
E28250
|
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: Taejon (Daejeon), South Korea | Statement: [Nagano, hasSisterCity, Taejon (Daejeon), South Korea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taejon (Daejeon), South Korea Context triple: [Nagano, hasSisterCity, Taejon (Daejeon), South Korea]
-
A.
Daejeon
chosen
Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
-
B.
Gunsan, South Korea
Gunsan, South Korea is a coastal industrial city in North Jeolla Province known for its port, manufacturing facilities, and role as a regional transportation hub.
-
C.
Daegu
Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
-
D.
Gwangju
Gwangju is a major metropolitan city in southwestern South Korea known for its rich cultural heritage and pivotal role in the country’s pro-democracy movement.
-
E.
Jinju, South Korea
Jinju, South Korea is a historic city in South Gyeongsang Province known for its riverside fortress, role in the Imjin War, and annual lantern festival.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98002da4819098d6448eebcafad4 |
completed | March 8, 2026, 3:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b354505574819083ae7d36e461366b |
completed | March 13, 2026, 12:03 a.m. |
Created at: March 8, 2026, 2:55 p.m.