Triple
T4839120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangnam District |
E108134
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Samseong-dong
Samseong-dong is a prominent neighborhood in Seoul, South Korea, known for its upscale shopping, business centers, and major landmarks like COEX Mall.
|
E491570
|
NE FINISHED |
How this triple was built (4 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: Samseong-dong | Statement: [Gangnam District, contains, Samseong-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samseong-dong Context triple: [Gangnam District, contains, Samseong-dong]
-
A.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
B.
Millak-dong
Millak-dong is a coastal neighborhood in Busan, South Korea, known for its proximity to Gwangalli Beach and vibrant urban atmosphere.
-
C.
Segyo-dong
Segyo-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
D.
Geumsa-dong
Geumsa-dong is a neighborhood (dong) located within Geumjeong District in Busan, South Korea.
-
E.
Namcheon-dong
Namcheon-dong is a coastal neighborhood in Busan, South Korea, known for its residential areas, local markets, and proximity to Gwangalli Beach.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Samseong-dong Triple: [Gangnam District, contains, Samseong-dong]
Generated description
Samseong-dong is a prominent neighborhood in Seoul, South Korea, known for its upscale shopping, business centers, and major landmarks like COEX Mall.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samseong-dong Target entity description: Samseong-dong is a prominent neighborhood in Seoul, South Korea, known for its upscale shopping, business centers, and major landmarks like COEX Mall.
-
A.
Seongho-dong
Seongho-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
B.
Millak-dong
Millak-dong is a coastal neighborhood in Busan, South Korea, known for its proximity to Gwangalli Beach and vibrant urban atmosphere.
-
C.
Segyo-dong
Segyo-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
-
D.
Geumsa-dong
Geumsa-dong is a neighborhood (dong) located within Geumjeong District in Busan, South Korea.
-
E.
Namcheon-dong
Namcheon-dong is a coastal neighborhood in Busan, South Korea, known for its residential areas, local markets, and proximity to Gwangalli Beach.
- F. None of above. chosen
Provenance (5 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ce4a5108190aede620d5dde1f81 |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0cd44088190ba26171758898497 |
completed | March 21, 2026, 2:53 p.m. |
| NEDg | Description generation | batch_69beb21e4b6c8190bf800ee885557323 |
completed | March 21, 2026, 2:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69beb23f789c8190811ee9e43327196c |
completed | March 21, 2026, 2:59 p.m. |
Created at: March 20, 2026, 1:25 p.m.