Triple
T19445900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tongmyeongjeon Hall |
E486473
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Chundangji Pond |
—
|
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: Chundangji Pond | Statement: [Tongmyeongjeon Hall, near, Chundangji Pond]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chundangji Pond Context triple: [Tongmyeongjeon Hall, near, Chundangji Pond]
-
A.
Chundangji Pond
chosen
Chundangji Pond is a scenic historic pond and garden feature located within Changgyeonggung Palace in Seoul, South Korea.
-
B.
Buyongji Pond
Buyongji Pond is a scenic lotus pond and central feature of the tranquil Secret Garden within Changdeokgung Palace in Seoul, South Korea.
-
C.
Chungju Lake
Chungju Lake is a large artificial reservoir in South Korea, created by the Chungju Dam and known for its scenic landscapes and recreational activities.
-
D.
Gongjicheon Lake
Gongjicheon Lake is a scenic body of water in Chuncheon, South Korea, known for its riverside parks, walking paths, and seasonal festivals.
-
E.
Sanjeong Lake
Sanjeong Lake is a scenic highland lake in Pocheon, South Korea, known for its forested mountains, walking trails, and seasonal views that attract many visitors.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338a22608190bb31a1690ca0dab6 |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.