Triple
T6810207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyeryongsan |
E156609
|
entity |
| Predicate | hasPeak |
P8205
|
FINISHED |
| Object |
Sinseongbong
Sinseongbong is a prominent mountain peak located within the Gyeryongsan mountain range in South Korea.
|
E627487
|
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: Sinseongbong | Statement: [Gyeryongsan, hasPeak, Sinseongbong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sinseongbong Context triple: [Gyeryongsan, hasPeak, Sinseongbong]
-
A.
Wiryeseong
Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
-
B.
Donggureung
Donggureung is a large royal burial complex in Guri, South Korea, containing multiple tombs of Joseon Dynasty kings and queens and recognized as part of a UNESCO World Heritage site.
-
C.
Yeongdodaegyo
Yeongdodaegyo is a bascule bridge in Busan, South Korea, known as the city’s first mainland–island bridge and a local historical landmark.
-
D.
Gwangalli
Gwangalli is a coastal neighborhood in Busan, South Korea, best known for its sandy beach, vibrant nightlife, and scenic views of the nearby Gwangan Bridge.
-
E.
Won-dong
Won-dong is a neighborhood (dong) within 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: Sinseongbong Triple: [Gyeryongsan, hasPeak, Sinseongbong]
Generated description
Sinseongbong is a prominent mountain peak located within the Gyeryongsan mountain range in South Korea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sinseongbong Target entity description: Sinseongbong is a prominent mountain peak located within the Gyeryongsan mountain range in South Korea.
-
A.
Wiryeseong
Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
-
B.
Donggureung
Donggureung is a large royal burial complex in Guri, South Korea, containing multiple tombs of Joseon Dynasty kings and queens and recognized as part of a UNESCO World Heritage site.
-
C.
Yeongdodaegyo
Yeongdodaegyo is a bascule bridge in Busan, South Korea, known as the city’s first mainland–island bridge and a local historical landmark.
-
D.
Gwangalli
Gwangalli is a coastal neighborhood in Busan, South Korea, best known for its sandy beach, vibrant nightlife, and scenic views of the nearby Gwangan Bridge.
-
E.
Won-dong
Won-dong is a neighborhood (dong) within 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30ded6481908fd64611607c610e |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748ad80b881909efd0c0abddb95a5 |
completed | March 28, 2026, 3:19 a.m. |
| NEDg | Description generation | batch_69c749a44a3c8190ad8ad35fac7a4859 |
completed | March 28, 2026, 3:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c74a1935b88190a9bed6e73f730459 |
completed | March 28, 2026, 3:25 a.m. |
Created at: March 27, 2026, 2:16 p.m.