Triple
T19599060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AREX airport railroad |
E470419
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Gongdeok Station |
—
|
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: Gongdeok Station | Statement: [AREX airport railroad, hasStation, Gongdeok Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gongdeok Station Context triple: [AREX airport railroad, hasStation, Gongdeok Station]
-
A.
Gongdeok Station
chosen
Gongdeok Station is a major subway and airport railroad interchange station in Seoul, South Korea, connecting multiple metro lines with the AREX line to Incheon International Airport.
-
B.
Beomgye Station
Beomgye Station is a subway station in Anyang, South Korea, serving as a local transit hub on the Seoul metropolitan rail network.
-
C.
Dongsu Station
Dongsu Station is a major subway station in Incheon, South Korea, serving as an important transit hub within the city's metro network.
-
D.
Bonghwasan Station
Bonghwasan Station is a subway station in Seoul, South Korea, serving as the northeastern terminus of Seoul Subway Line 6.
-
E.
Bongcheon Station
Bongcheon Station is a subway station on Seoul Subway Line 2 serving the Bongcheon-dong area in Seoul, South Korea.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6407d46188190b9818665b2a698a5 |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.