Triple
T25646065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeonsu-dong |
E642968
|
entity |
| Predicate | roadAddressSystem |
P1216
|
FINISHED |
| Object | South Korean road name address system |
—
|
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: South Korean road name address system | Statement: [Yeonsu-dong, roadAddressSystem, South Korean road name address system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadAddressSystem Context triple: [Yeonsu-dong, roadAddressSystem, South Korean road name address system]
-
A.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
B.
roadName
Indicates the specific name assigned to a road that identifies it within a transportation or address system.
-
C.
roadSystemLevel
Indicates the classification or hierarchy level of a road within a broader transportation or road network system.
-
D.
usesAddressingSystem
chosen
Indicates that one entity employs or applies a particular addressing system associated with another entity.
-
E.
hasStreetNumberingSystem
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
- F. None of above.
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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5faa437a481908d89a553f2406161 |
completed | May 2, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 5:53 p.m.