Triple
T19540524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sareung (Namyangju) |
E488885
|
entity |
| Predicate | hasKoreanNameScript |
P5233
|
FINISHED |
| Object | Hangul |
—
|
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: Hangul | Statement: [Sareung (Namyangju), hasKoreanNameScript, Hangul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKoreanNameScript Context triple: [Sareung (Namyangju), hasKoreanNameScript, Hangul]
-
A.
hasUnicodeScript
chosen
Indicates that a character or text element belongs to a specific Unicode script category (such as Latin, Cyrillic, or Han).
-
B.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
-
C.
hasKoreanVersion
Indicates that something has a corresponding version or counterpart that is in the Korean language.
-
D.
hasUnicodeName
Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
-
E.
hasHakkaRomanization
Indicates that an entity is associated with a specific representation of its name or term in Hakka Romanization.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63872fda48190bbb1f465cb7b57fe |
completed | April 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69e514c9c00481909b76bda67957e58b |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.