Triple
T20796150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daegu |
E511913
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Nam District
Nam District is an administrative district (gu) located in the city of Daegu, South Korea.
|
E1456164
|
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: Nam District | Statement: [Daegu, hasDistrict, Nam District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nam District Context triple: [Daegu, hasDistrict, Nam District]
-
A.
Nam District
Nam District is an administrative district (gu) of the metropolitan city of Busan in South Korea, known for its coastal location and urban residential areas.
-
B.
Amuria District
Amuria District is an administrative district in northeastern Uganda known for its predominantly rural communities and agriculture-based economy.
-
C.
Sumowono District
Sumowono District is an administrative district in Central Java, Indonesia, located within Semarang Regency and known for its cool highland climate and rural communities.
-
D.
Namatanai District
Namatanai District is an administrative district located on the island of New Ireland in Papua New Guinea, encompassing rural communities, coastal areas, and local government centers.
-
E.
Chikan District
Chikan District is an urban administrative district and central area of Zhanjiang City in Guangdong Province, China.
- 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: Nam District Triple: [Daegu, hasDistrict, Nam District]
Generated description
Nam District is an administrative district (gu) located in the city of Daegu, South Korea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nam District Target entity description: Nam District is an administrative district (gu) located in the city of Daegu, South Korea.
-
A.
Nam District
Nam District is an administrative district (gu) of the metropolitan city of Busan in South Korea, known for its coastal location and urban residential areas.
-
B.
Amuria District
Amuria District is an administrative district in northeastern Uganda known for its predominantly rural communities and agriculture-based economy.
-
C.
Sumowono District
Sumowono District is an administrative district in Central Java, Indonesia, located within Semarang Regency and known for its cool highland climate and rural communities.
-
D.
Namatanai District
Namatanai District is an administrative district located on the island of New Ireland in Papua New Guinea, encompassing rural communities, coastal areas, and local government centers.
-
E.
Chikan District
Chikan District is an urban administrative district and central area of Zhanjiang City in Guangdong Province, China.
- 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2ad6f0481909e0bab7119f10f9c |
completed | April 21, 2026, 12:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0918bc01588190b12722d6cd9b1f4a |
completed | May 17, 2026, 1:24 a.m. |
| NEDg | Description generation | batch_6a0919608d148190aaf1abee12fe8935 |
completed | May 17, 2026, 1:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0919f58008819097e05a187ed4b3de |
completed | May 17, 2026, 1:29 a.m. |
Created at: April 16, 2026, 12:39 p.m.