Triple
T24123596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeongju Kim clan |
E597729
|
entity |
| Predicate | hasBonGwanInHanja |
P27905
|
FINISHED |
| Object | 慶州 |
—
|
NE NERFINISHED |
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: 慶州 | Statement: [Gyeongju Kim clan, hasBonGwanInHanja, 慶州]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBonGwanInHanja Context triple: [Gyeongju Kim clan, hasBonGwanInHanja, 慶州]
-
A.
hanjaName
chosen
Indicates that one entity is the Sino-Korean (hanja) written form corresponding to the name of another entity.
-
B.
hasHangulName
Indicates that an entity is associated with a name written in the Korean Hangul script.
-
C.
usesHanjaVariants
Indicates that one entity employs or incorporates alternative Hanja (Chinese character) forms corresponding to another entity.
-
D.
hasTraditionalCharacter
Indicates that an entity is associated with or represented by a traditional (non-simplified or historically established) written character form.
-
E.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
- 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_69e288c808b881909fed7d18f04bcbbe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dee718f88190860d40c6f09a77c8 |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:06 p.m.