Triple
T20209760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Later Goguryeo |
E493457
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Taebong |
—
|
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: Taebong | Statement: [Later Goguryeo, alsoKnownAs, Taebong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taebong Context triple: [Later Goguryeo, alsoKnownAs, Taebong]
-
A.
Taebong
chosen
Taebong was a short-lived Korean kingdom of the early 10th century that emerged during the Later Three Kingdoms period before being absorbed by Goryeo.
-
B.
Tancheon
Tancheon is a river in South Korea that flows through the city of Seongnam and serves as a key urban waterway and recreational area.
-
C.
Nakchhong
Nakchhong is a traditional ritual specialist and religious officiant within the Kirat Mundhum indigenous belief system.
-
D.
Phyongwon
Phyongwon is a city in North Korea known as an administrative and agricultural center within North Pyongan Province.
-
E.
Seogwipo
Seogwipo is a coastal city on South Korea’s Jeju Island known for its waterfalls, volcanic landscapes, and popular tourist attractions.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ed4706c81908a5e4a3023a9c22f |
completed | April 20, 2026, 6:22 p.m. |
Created at: April 11, 2026, 11:38 p.m.