Triple
T20407243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celje |
E500500
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Gwangmyeong |
—
|
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: Gwangmyeong | Statement: [Celje, hasTwinTown, Gwangmyeong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gwangmyeong Context triple: [Celje, hasTwinTown, Gwangmyeong]
-
A.
Gwangmyeong
chosen
Gwangmyeong is a city in South Korea known for its proximity to Seoul and attractions like the Gwangmyeong Cave, a former mine turned cultural and tourism complex.
-
B.
Hwaseong-si
Hwaseong-si is a rapidly growing city in Gyeonggi Province, South Korea, known for its industrial complexes, coastal wetlands, and proximity to Seoul.
-
C.
Gapyeong
Gapyeong is a county in South Korea’s Gyeonggi Province known for its scenic riverside landscapes, tourist attractions like Nami Island and the Garden of Morning Calm, and easy access from Seoul.
-
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.
Tancheon
Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67993dc7081908ebd54ec92e712ea |
completed | April 20, 2026, 7:08 p.m. |
Created at: April 16, 2026, 11:29 a.m.