Triple
T17851436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangneung |
E445814
|
entity |
| Predicate | administrativeDivisionOf |
P747
|
FINISHED |
| Object | Gangneung-si |
—
|
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: Gangneung-si | Statement: [Gangneung, administrativeDivisionOf, Gangneung-si]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gangneung-si Context triple: [Gangneung, administrativeDivisionOf, Gangneung-si]
-
A.
Gangneung
chosen
Gangneung is a coastal city in South Korea’s Gangwon Province, known for its beaches, cultural festivals, and role as a host city during the 2018 Pyeongchang Winter Olympics.
-
B.
Wonju
Wonju is a city in South Korea’s Gangwon Province known historically as a strategic military site and today as a regional commercial and transportation hub.
-
C.
Pyeongtaek
Pyeongtaek is a South Korean city in Gyeonggi Province known for its major U.S. and UN military presence, including large bases such as Camp Humphreys.
-
D.
Icheon
Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
-
E.
Yeoju
Yeoju is a city in South Korea known for its rich historical heritage, including royal tombs and ceramics, and its scenic riverside landscapes.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48fff6c288190a2b5e60b66c03ddc |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:17 a.m.