Triple
T11525691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoullo 7017 |
E273288
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Seoul Station |
E467238
|
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: Seoul Station | Statement: [Seoullo 7017, locatedNear, Seoul Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seoul Station Context triple: [Seoullo 7017, locatedNear, Seoul Station]
-
A.
Seoul Station
chosen
Seoul Station is a major railway and transportation hub in central Seoul, South Korea, serving high-speed, intercity, and commuter trains as well as multiple subway lines.
-
B.
Incheon Station
Incheon Station is a major railway and subway terminus in the city of Incheon, South Korea, serving as an important transportation hub in the greater Seoul metropolitan area.
-
C.
Yeonsan Station
Yeonsan Station is a major transit hub in Busan, South Korea, serving as an important interchange point on the city’s subway network.
-
D.
Songjeong Station
Songjeong Station is a railway station in Busan, South Korea, serving as a convenient transit point for visitors traveling to the nearby coastal area of Songjeong Beach.
-
E.
Daejeon Station
Daejeon Station is a major railway hub in central South Korea, serving high-speed KTX trains and connecting Daejeon to key cities nationwide.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fd379648190b342e0c4b4f685b7 |
completed | April 10, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e62562efb88190bbf3c7bbec8233aa |
completed | April 20, 2026, 1:08 p.m. |
Created at: April 8, 2026, 9:37 p.m.