Triple
T27846988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 윤여정 |
E703851
|
entity |
| Predicate | 로마자 표기 |
P105016
|
FINISHED |
| Object | Youn Yuh-jung |
—
|
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: Youn Yuh-jung | Statement: [윤여정, 로마자 표기, Youn Yuh-jung]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 로마자 표기 Context triple: [윤여정, 로마자 표기, Youn Yuh-jung]
-
A.
laterRomanizedInto
Indicates that an entity’s original form (such as a name, word, or title) was subsequently converted into a later Romanized (Latin-script) version.
-
B.
exampleRomanization
Indicates that one entity is a romanized representation (in Latin script) of the other entity’s original text or name.
-
C.
romanizationVariantOf
Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
-
D.
hangulNameRomanized
chosen
Indicates that an entity’s Korean Hangul name is represented in its romanized (Latin alphabet) form.
-
E.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63902060081909bb490327b0c16f2 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 6:08 p.m.