Triple
T21868666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yi Do |
E539947
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object | Yeoju |
—
|
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: Yeoju | Statement: [Yi Do, burialPlace, Yeoju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeoju Context triple: [Yi Do, burialPlace, Yeoju]
-
A.
Yeoju
chosen
Yeoju is a city in South Korea known for its rich historical heritage, including royal tombs and ceramics, and its scenic riverside landscapes.
-
B.
Jeonju
Jeonju is a historic city in southwestern South Korea known for its well-preserved Hanok Village, rich culinary traditions, and cultural heritage.
-
C.
Sacheon
Sacheon is a coastal city in South Gyeongsang Province, South Korea, known for its fishing industry, maritime transport, and aerospace manufacturing.
-
D.
Suncheon
Suncheon is a city in South Jeolla Province, South Korea, known for its ecological attractions such as the Suncheon Bay Wetland Reserve and its role as a regional administrative and cultural center.
-
E.
Jeongeup
Jeongeup is a city in South Korea known for its location in North Jeolla Province and its cultural and historical heritage.
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f33305d081908cd070134420607a |
completed | April 28, 2026, 5:49 p.m. |
Created at: April 16, 2026, 6:57 p.m.