Triple
T14886533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jongno District |
E350135
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Insa-dong
Insa-dong is a popular neighborhood in central Seoul known for its traditional Korean culture, antique shops, art galleries, and teahouses.
|
E1184786
|
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: Insa-dong | Statement: [Jongno District, contains, Insa-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Insa-dong Context triple: [Jongno District, contains, Insa-dong]
-
A.
Cheonghak-dong
Cheonghak-dong is a neighborhood (dong) located within Dong-gu, one of the central districts of Busan, South Korea.
-
B.
Cheonghak-dong
Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
-
C.
Hwanghak-dong
Hwanghak-dong is a neighborhood in central Seoul, South Korea, known for its traditional flea markets and dense urban streetscape.
-
D.
Sinsa-dong
Sinsa-dong is a fashionable neighborhood in Seoul, South Korea, known for its trendy boutiques, cafes, and the popular Garosu-gil shopping street.
-
E.
Yongho-dong
Yongho-dong is a neighborhood in Busan, South Korea, known as a coastal residential area within the city's southern region.
- 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: Insa-dong Triple: [Jongno District, contains, Insa-dong]
Generated description
Insa-dong is a popular neighborhood in central Seoul known for its traditional Korean culture, antique shops, art galleries, and teahouses.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Insa-dong Target entity description: Insa-dong is a popular neighborhood in central Seoul known for its traditional Korean culture, antique shops, art galleries, and teahouses.
-
A.
Cheonghak-dong
Cheonghak-dong is a neighborhood (dong) located within Dong-gu, one of the central districts of Busan, South Korea.
-
B.
Cheonghak-dong
Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
-
C.
Hwanghak-dong
Hwanghak-dong is a neighborhood in central Seoul, South Korea, known for its traditional flea markets and dense urban streetscape.
-
D.
Sinsa-dong
Sinsa-dong is a fashionable neighborhood in Seoul, South Korea, known for its trendy boutiques, cafes, and the popular Garosu-gil shopping street.
-
E.
Yongho-dong
Yongho-dong is a neighborhood in Busan, South Korea, known as a coastal residential area within the city's southern region.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5f5b1c88190815f3585770cb135 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb590b5cc8190b5f586e0fd2988f6 |
completed | May 9, 2026, 10:30 p.m. |
| NEDg | Description generation | batch_69ffb792ebe88190a112a86a3b2dc6ea |
completed | May 9, 2026, 10:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb7dfbec08190939cdeaf46ea15ae |
completed | May 9, 2026, 10:40 p.m. |
Created at: April 10, 2026, 1:56 a.m.