Triple
T15200589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 오산시 |
E363256
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | 오산천 |
E388784
|
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: 오산천 | Statement: [오산시, hasRiver, 오산천]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 오산천 Context triple: [오산시, hasRiver, 오산천]
-
A.
Anseongcheon
Anseongcheon is a river in South Korea that flows through the city of Pyeongtaek in Gyeonggi Province.
-
B.
Oncheoncheon Stream
Oncheoncheon Stream is an urban waterway in Busan, South Korea, known for its riverside parks, walking paths, and proximity to historic sites such as Geumjeong Fortress.
-
C.
Daegokcheon stream
Daegokcheon stream is a watercourse in Ulsan, South Korea, known for flowing past the Bangudae Petroglyphs, a major prehistoric rock art site.
-
D.
Hwanggujicheon
chosen
Hwanggujicheon is a stream in Osan, South Korea, that serves as a local waterway and natural feature of the city’s landscape.
-
E.
Hwangnyeongsan
Hwangnyeongsan is a mountain in Busan, South Korea, known for its panoramic city views and popular hiking trails.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b588b88190a88e91d521acbdfe |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed3363f688190a5c728846bea743a |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 3:10 a.m.