Triple
T23218590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangneung Station |
E580819
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Gangneung city |
—
|
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 city | Statement: [Gangneung Station, serves, Gangneung city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gangneung city Context triple: [Gangneung Station, serves, Gangneung city]
-
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.
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.
-
C.
Pyeongchang-eup
Pyeongchang-eup is the main urban township and administrative center of Pyeongchang County in Gangwon Province, South Korea.
-
D.
Gimcheon
Gimcheon is a city in North Gyeongsang Province, South Korea, known as a regional transportation hub and administrative center.
-
E.
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.
- 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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f191675de48190858907872a065c56 |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:08 p.m.