Triple
T9590323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimilsungia |
E231398
|
entity |
| Predicate | languageOfOriginOfName |
P1754
|
FINISHED |
| Object | Korean |
—
|
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: Korean | Statement: [Kimilsungia, languageOfOriginOfName, Korean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOriginOfName Context triple: [Kimilsungia, languageOfOriginOfName, Korean]
-
A.
nameEtymologyFor
Indicates that one entity expresses or explains the origin or derivation of the name of another entity.
-
B.
possibleNameEtymology
Indicates a hypothesized or suggested origin or derivation of an entity’s name from another term, source, or linguistic root.
-
C.
originalNameMeaningSource
Indicates that there is a source or reference that explains or provides the meaning of an entity’s original name.
-
D.
hasLanguageOfOrigin
chosen
Indicates that one entity has its origin or source in the language specified by another entity.
-
E.
nameMeaningLanguage
Indicates that a specified meaning of a name is expressed or interpreted in a particular language.
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99f32e688190bb13bccfa5031f16 |
completed | April 1, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69ccd59fd7408190b36831902e3f37f7 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:06 p.m.