Triple
T6686499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Gyeongsang Province |
E152110
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Andong |
E531413
|
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: Andong | Statement: [North Gyeongsang Province, capital, Andong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andong Context triple: [North Gyeongsang Province, capital, Andong]
-
A.
Andong
chosen
Andong is a historic city in South Korea renowned for its preserved traditional culture, including the Hahoe Folk Village and the Andong Mask Dance Festival.
-
B.
Yeoju
Yeoju is a city in South Korea known for its rich historical heritage, including royal tombs and ceramics, and its scenic riverside landscapes.
-
C.
Gwangmyeong
Gwangmyeong is a city in South Korea known for its proximity to Seoul and attractions like the Gwangmyeong Cave, a former mine turned cultural and tourism complex.
-
D.
Namyangju
Namyangju is a city in South Korea known for its scenic natural landscapes, historical sites, and role as a suburban area within the Seoul metropolitan region.
-
E.
Icheon
Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b14cd6748190aad4badd5f253478 |
completed | March 27, 2026, 4:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7942437bc8190808e60d12b98dcf5 |
completed | March 28, 2026, 8:41 a.m. |
Created at: March 27, 2026, 2:04 p.m.