Triple
T27044829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuseong Hot Springs |
E684592
|
entity |
| Predicate | waterIsKnownFor |
P172351
|
FINISHED |
| Object | therapeutic mineral waters |
—
|
LITERAL 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: therapeutic mineral waters | Statement: [Yuseong Hot Springs, waterIsKnownFor, therapeutic mineral waters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterIsKnownFor Context triple: [Yuseong Hot Springs, waterIsKnownFor, therapeutic mineral waters]
-
A.
waterbodyUsedFor
Indicates that a particular water body is utilized for a specific purpose, activity, or function.
-
B.
bodyOfWater
Indicates that one entity is a body of water that is geographically or physically associated with another entity.
-
C.
waterContains
Indicates that a body or volume of water holds, includes, or has within it a specified substance, object, or entity.
-
D.
hasWatersOf
Indicates that a geographic or physical entity contains, is traversed by, or is otherwise characterized by specific bodies or types of water.
-
E.
formsBodyOfWater
Indicates that one entity constitutes or creates the physical substance or structure that makes up a particular body of water.
- F. None of above. chosen
Provenance (4 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_69ef148193c48190bb1a0cfae6a407c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f6abe15d5c81909ccf4ce37f78bc43 |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1c555081908787dbf76147f180 |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aaf31a548190b2f792ff4b8c002a |
completed | May 3, 2026, 1:54 a.m. |
Created at: April 27, 2026, 8:09 a.m.