Triple
T9294136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yongsan Garrison |
E223596
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Itaewon |
E109253
|
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: Itaewon | Statement: [Yongsan Garrison, near, Itaewon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itaewon Context triple: [Yongsan Garrison, near, Itaewon]
-
A.
Itaewon
chosen
Itaewon is a vibrant multicultural district in Seoul known for its international cuisine, nightlife, and diverse expatriate community.
-
B.
Hongdae
Hongdae is a vibrant neighborhood in Seoul known for its indie music scene, street art, nightlife, and youth culture centered around Hongik University.
-
C.
Myeongdong
Myeongdong is a major shopping and entertainment district in central Seoul, famous for its fashion boutiques, street food, and vibrant nightlife.
-
D.
Songdo-dong
Songdo-dong is a modern waterfront neighborhood in Incheon, South Korea, best known for hosting the high-tech, master-planned Songdo International Business District.
-
E.
Cheongdam-dong
Cheongdam-dong is an affluent neighborhood in Seoul known for its luxury boutiques, high-end residences, and trendy cafes and galleries.
- 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd089a2ed0819086b2e4219ff2453e |
completed | April 1, 2026, 11:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e3865ef081909f5f258cac44ae8b |
completed | April 4, 2026, 10:10 a.m. |
Created at: March 30, 2026, 7:35 p.m.