Triple
T20790778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Seong of Baekje |
E511769
|
entity |
| Predicate | personalName |
P24312
|
FINISHED |
| Object | Seong |
—
|
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: Seong | Statement: [King Seong of Baekje, personalName, Seong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seong Context triple: [King Seong of Baekje, personalName, Seong]
-
A.
Seong
chosen
Seong is a Korean family name shared by various individuals in Korea and the Korean diaspora.
-
B.
Seonghwa
Seonghwa was the era name used during the reign of King Seongjong of the Joseon dynasty in Korea, marking a specific period of his rule.
-
C.
Jeong
Jeong is a Korean given name commonly used for both males and females, often associated with meanings related to affection, virtue, or righteousness depending on the hanja used.
-
D.
Jeong
Jeong is the Korean family name of Ken Jeong, the American comedian, actor, and physician known for roles in "The Hangover" series and the TV show "Community."
-
E.
Seonghwan
Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c29010508190bf2cf577d7f64754 |
completed | April 21, 2026, 12:19 a.m. |
Created at: April 16, 2026, 12:38 p.m.