Triple
T28269419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 蔣 |
E712801
|
entity |
| Predicate | transliterationInKoreanHanja |
P27905
|
FINISHED |
| Object | 장 (Jang) |
—
|
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: 장 (Jang) | Statement: [蔣, transliterationInKoreanHanja, 장 (Jang)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transliterationInKoreanHanja Context triple: [蔣, transliterationInKoreanHanja, 장 (Jang)]
-
A.
hanjaName
chosen
Indicates that one entity is the Sino-Korean (hanja) written form corresponding to the name of another entity.
-
B.
equivalentInJapaneseKanji
Indicates that one entity has the same meaning or value as another entity when written in Japanese Kanji.
-
C.
formerTransliteration
Indicates that one transliteration was previously used for an entity but has since been replaced by a different transliteration.
-
D.
hangulNameRomanized
Indicates that an entity’s Korean Hangul name is represented in its romanized (Latin alphabet) form.
-
E.
koreanReadingHangul
Indicates that an entity’s Korean reading is represented in Hangul script.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: April 27, 2026, 11:17 p.m.