Triple
T19116776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gimpo International Airport |
E467926
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Goyang |
—
|
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: Goyang | Statement: [Gimpo International Airport, cityServed, Goyang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goyang Context triple: [Gimpo International Airport, cityServed, Goyang]
-
A.
Goyang
chosen
Goyang is a major satellite city northwest of Seoul in South Korea, known for its rapid urban development, residential districts, and cultural attractions such as Ilsan Lake Park and KINTEX.
-
B.
Honam
Honam is a southwestern region of South Korea known for its rich agricultural land, distinct cultural traditions, and major cities like Gwangju and Jeonju.
-
C.
Gwangyang
Gwangyang is an industrial port city in South Korea known for its major steelworks complex and scenic coastal and mountainous landscapes.
-
D.
Yangju
Yangju is a city in northwestern South Korea known for its mix of suburban residential areas, light industry, and proximity to Seoul.
-
E.
Miryang
Miryang is a city in South Gyeongsang Province, South Korea, known for its scenic river valley setting, historical sites, and role as a regional transport and educational 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3984bf48190818fa2b01b75decb |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:05 p.m.