Triple
T1359021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasang District |
E29055
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Jurye-dong
Jurye-dong is a neighborhood (dong) in Busan, South Korea, known as a residential and commercial area within the city's Sasang District.
|
E188156
|
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: Jurye-dong | Statement: [Sasang District, contains, Jurye-dong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jurye-dong Context triple: [Sasang District, contains, Jurye-dong]
-
A.
Gamjeon-dong
Gamjeon-dong is a neighborhood in the Sasang District of Busan, South Korea, known as a residential and commercial area within the city.
-
B.
Gwaebeop-dong
Gwaebeop-dong is a neighborhood in Busan, South Korea, known as an administrative subdivision of the city's Sasang District.
-
C.
Ami-dong
Ami-dong is a neighborhood in Busan, South Korea, known in part for hosting a campus of Pusan National University.
-
D.
Dong-gu
Dong-gu is an administrative district of the metropolitan city of Ulsan in South Korea, known for its coastal location and industrial facilities.
-
E.
Dong-gu
Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
- 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: Jurye-dong Triple: [Sasang District, contains, Jurye-dong]
Generated description
Jurye-dong is a neighborhood (dong) in Busan, South Korea, known as a residential and commercial area within the city's Sasang District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jurye-dong Target entity description: Jurye-dong is a neighborhood (dong) in Busan, South Korea, known as a residential and commercial area within the city's Sasang District.
-
A.
Gamjeon-dong
Gamjeon-dong is a neighborhood in the Sasang District of Busan, South Korea, known as a residential and commercial area within the city.
-
B.
Gwaebeop-dong
Gwaebeop-dong is a neighborhood in Busan, South Korea, known as an administrative subdivision of the city's Sasang District.
-
C.
Ami-dong
Ami-dong is a neighborhood in Busan, South Korea, known in part for hosting a campus of Pusan National University.
-
D.
Dong-gu
Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
-
E.
Dong-gu
Dong-gu is an administrative district of the metropolitan city of Ulsan in South Korea, known for its coastal location and industrial facilities.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c290db288190910fcfa17e902663 |
completed | March 1, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad67ff7fe481908e1705ba8be84f3a |
completed | March 8, 2026, 12:13 p.m. |
| NEDg | Description generation | batch_69ad6918ebd4819085cd74c172e5c72e |
completed | March 8, 2026, 12:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad697d0edc8190b94e61b57f0c65ee |
completed | March 8, 2026, 12:20 p.m. |
Created at: March 1, 2026, 7:56 p.m.