Triple
T11745084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawagoe |
E279257
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Paju, South Korea |
E473117
|
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: Paju, South Korea | Statement: [Kawagoe, hasSisterCity, Paju, South Korea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paju, South Korea Context triple: [Kawagoe, hasSisterCity, Paju, South Korea]
-
A.
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.
-
B.
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.
-
C.
Suwon, South Korea
Suwon, South Korea is a major city just south of Seoul known for its high-tech industry and the UNESCO-listed Hwaseong Fortress.
-
D.
Paju, Gyeonggi Province
chosen
Paju, in Gyeonggi Province, is a South Korean border city near the Demilitarized Zone known for sites like the Dorasan area and its symbolic role in inter-Korean relations.
-
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 (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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f2a38c8190a682d8dae1ab9415 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f019e4f0988190afe0b92f4c9d8073 |
completed | April 28, 2026, 2:22 a.m. |
Created at: April 8, 2026, 9:41 p.m.