Triple
T8362729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeonsan Station |
E197048
|
entity |
| Predicate | servesLocality |
P26183
|
FINISHED |
| Object | Yeonsan-dong |
E315908
|
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: Yeonsan-dong | Statement: [Yeonsan Station, servesLocality, Yeonsan-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeonsan-dong Context triple: [Yeonsan Station, servesLocality, Yeonsan-dong]
-
A.
Yeonsan-dong
chosen
Yeonsan-dong is a neighborhood-level administrative area within Yeonje District in Busan, South Korea, known for its residential zones and local commercial facilities.
-
B.
Yeonsu-dong
Yeonsu-dong is a neighborhood within Incheon, South Korea, known as a residential and local commercial area of Yeonsu District.
-
C.
Yeocheon-dong
Yeocheon-dong is a neighborhood in Ulsan, South Korea, known for encompassing the expansive Ulsan Grand Park.
-
D.
Yeoksam-dong
Yeoksam-dong is a major commercial and residential neighborhood in Seoul, South Korea, known for its dense cluster of corporate offices, tech companies, and vibrant urban amenities.
-
E.
Okryeon-dong
Okryeon-dong is a neighborhood located within Yeonsu District in Incheon, South Korea.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80768b208190a5f6c9e6cb6e7f30 |
completed | March 31, 2026, 8:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d121b5cc1c819093109b22acacf98f |
completed | April 4, 2026, 2:35 p.m. |
Created at: March 30, 2026, 6 p.m.