Triple
T23138611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .kr |
E577393
|
entity |
| Predicate | commercialSecondLevelDomain |
P151058
|
FINISHED |
| Object | .co.kr |
—
|
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: .co.kr | Statement: [.kr, commercialSecondLevelDomain, .co.kr]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commercialSecondLevelDomain Context triple: [.kr, commercialSecondLevelDomain, .co.kr]
-
A.
secondLevelDomain
Indicates that one entity is the second-level domain associated with, or extracted from, another entity such as a full domain name or URL.
-
B.
exampleSecondLevelDomain
Indicates that one entity is an example of a second-level domain (the part of a domain name directly below a top-level domain) associated with another entity.
-
C.
secondaryDomain
Indicates that one domain functions as a secondary or auxiliary domain in relation to a primary domain.
-
D.
commercialService
Indicates a relationship where one entity provides a paid, profit-oriented service to another entity.
-
E.
commercialCategory
Indicates the type of commercial classification or business category under which an entity or transaction is grouped.
- 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_69e245f8e6248190ba3d58e068b4dccb |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e8e23988190814524f63a7efe36 |
completed | April 29, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4 p.m.