Triple
T20413236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jumong |
E500641
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Buyeo |
—
|
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: Buyeo | Statement: [Jumong, associatedWith, Buyeo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buyeo Context triple: [Jumong, associatedWith, Buyeo]
-
A.
Buyeo
chosen
Buyeo was an ancient Korean kingdom that emerged in northern Manchuria and northern Korea, playing a key role in the early formation of Korean states and culture.
-
B.
Pakchon
Pakchon is a city in North Pyongan Province, North Korea, known as a regional center for agriculture and light industry.
-
C.
Buyeo-eup
Buyeo-eup is a town in South Chungcheong Province, South Korea, known for its rich Baekje-era heritage and numerous historical and archaeological sites.
-
D.
Yeongju
Yeongju is a city in eastern South Korea known for its historic temples, Confucian academies, and scenic mountainous landscapes.
-
E.
Meiktila
Meiktila is a city in central Myanmar that served as a key strategic location during World War II, particularly in the Burma Campaign.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a417f208190be9bc11650ee0a87 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:30 a.m.