Triple
T105879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korea under Japanese rule |
E2135
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Keijō |
E19209
|
NE FINISHED |
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: Keijō | Statement: [Korea under Japanese rule, capital, Keijō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keijō Context triple: [Korea under Japanese rule, capital, Keijō]
-
A.
Nara
Nara is an ancient Japanese city renowned for its early role as a national capital, its historic temples, and its culturally significant deer-filled parks.
-
B.
Seoul
chosen
Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
-
C.
Hanyang
Hanyang is a historic district and former city now incorporated into Wuhan in Hubei Province, China, known for its early industrial development and strategic location at the confluence of the Han and Yangtze rivers.
-
D.
Kyoto
Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
-
E.
Busan
Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a256c96e5481908c67f69e99978292 |
completed | Feb. 28, 2026, 2:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2d72fb0848190bf1f90c556af5f51 |
completed | Feb. 28, 2026, 11:53 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.