Triple
T23579425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korea |
E582155
|
entity |
| Predicate | traditionalScriptName |
P63723
|
FINISHED |
| Object | Hangul |
—
|
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: Hangul | Statement: [Korea, traditionalScriptName, Hangul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalScriptName Context triple: [Korea, traditionalScriptName, Hangul]
-
A.
traditionalCasing
Indicates that an entity uses or is presented in its historically established or customary letter casing, as opposed to a modified or nonstandard casing.
-
B.
formerScript
Indicates that an entity previously served as the script or writing system for another entity, but is no longer used in that role.
-
C.
nativeNameScript
chosen
Indicates the writing system or script in which an entity’s native name is expressed.
-
D.
traditionalStyle
Indicates that something follows or embodies a conventional, long-established way of doing, making, or presenting it, in contrast to modern or innovative styles.
-
E.
traditionalLanguageName
Indicates the name traditionally used in a particular language to refer to the subject entity.
- 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_69e248f8d8248190acd5aee77f0d1709 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1afd8e5ec81909fbdcf68bc14078e |
completed | April 29, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69f118bcc0b08190b25a8dddfd461a0e |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:39 p.m.