Triple
T17006747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheom |
E412589
|
entity |
| Predicate | correspondsToHanja |
P27905
|
FINISHED |
| Object | 詹 |
—
|
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: 詹 | Statement: [Cheom, correspondsToHanja, 詹]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToHanja Context triple: [Cheom, correspondsToHanja, 詹]
-
A.
hanjaName
chosen
Indicates that one entity is the Sino-Korean (hanja) written form corresponding to the name of another entity.
-
B.
correspondsToChineseCharacter
Indicates that one entity is the equivalent or representation of a specific Chinese written character.
-
C.
usesHanjaVariants
Indicates that one entity employs or incorporates alternative Hanja (Chinese character) forms corresponding to another entity.
-
D.
correspondsToChineseSurname
Indicates that one entity is the Chinese surname equivalent or counterpart of another entity.
-
E.
hasTraditionalCharacter
Indicates that an entity is associated with or represented by a traditional (non-simplified or historically established) written character form.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d3831268819089286053a5acf653 |
completed | April 18, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.