Triple
T5980322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monument to Party Founding |
E133102
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object |
Munsu Street
Munsu Street is a major thoroughfare in Pyongyang, North Korea, known for hosting prominent political monuments and state landmarks.
|
E559417
|
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: Munsu Street | Statement: [Monument to Party Founding, locatedOn, Munsu Street]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Munsu Street Context triple: [Monument to Party Founding, locatedOn, Munsu Street]
-
A.
Cheongnyong-dong
Cheongnyong-dong is a neighborhood located within Geumjeong District in Busan, South Korea.
-
B.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
-
C.
Cheonghak-dong
Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
-
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.
Gocheon-dong
Gocheon-dong is a neighborhood (dong) that forms part of the city of Osan in Gyeonggi Province, 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: Munsu Street Triple: [Monument to Party Founding, locatedOn, Munsu Street]
Generated description
Munsu Street is a major thoroughfare in Pyongyang, North Korea, known for hosting prominent political monuments and state landmarks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Munsu Street Target entity description: Munsu Street is a major thoroughfare in Pyongyang, North Korea, known for hosting prominent political monuments and state landmarks.
-
A.
Cheongnyong-dong
Cheongnyong-dong is a neighborhood located within Geumjeong District in Busan, South Korea.
-
B.
Yangjeong-dong
Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
-
C.
Cheonghak-dong
Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
-
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.
Gocheon-dong
Gocheon-dong is a neighborhood (dong) that forms part of the city of Osan in Gyeonggi Province, South Korea.
- 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a67c3248190ba35a7121eb49672 |
completed | March 22, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e42174a88190b8b40cbc7815911f |
completed | March 23, 2026, 6:56 a.m. |
| NEDg | Description generation | batch_69c0f602b79881909a6d971972f760b1 |
completed | March 23, 2026, 8:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0f6a75b908190b35d13b9593cf21f |
completed | March 23, 2026, 8:15 a.m. |
Created at: March 22, 2026, 4:04 p.m.