Triple
T14506791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nonsan |
E340283
|
entity |
| Predicate | hasRevisedRomanization |
P23170
|
FINISHED |
| Object |
Nonsan-si
Nonsan-si is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
|
E1105571
|
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: Nonsan-si | Statement: [Nonsan, hasRevisedRomanization, Nonsan-si]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nonsan-si Context triple: [Nonsan, hasRevisedRomanization, Nonsan-si]
-
A.
Sinseongbong
Sinseongbong is a prominent mountain peak located within the Gyeryongsan mountain range in South Korea.
-
B.
Myeong-bok
Myeong-bok is the given name of Gojong, the 26th king of the Joseon dynasty and first emperor of the Korean Empire.
-
C.
Wiryeseong
Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
-
D.
Sungsang
Sungsang is a coastal village in South Sumatra, Indonesia, known as a fishing and port settlement near the mouth of the Musi River.
-
E.
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.
- 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: Nonsan-si Triple: [Nonsan, hasRevisedRomanization, Nonsan-si]
Generated description
Nonsan-si is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nonsan-si Target entity description: Nonsan-si is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
-
A.
Sinseongbong
Sinseongbong is a prominent mountain peak located within the Gyeryongsan mountain range in South Korea.
-
B.
Myeong-bok
Myeong-bok is the given name of Gojong, the 26th king of the Joseon dynasty and first emperor of the Korean Empire.
-
C.
Wiryeseong
Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
-
D.
Sungsang
Sungsang is a coastal village in South Sumatra, Indonesia, known as a fishing and port settlement near the mouth of the Musi River.
-
E.
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.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e40e44819084f323f8f9982b75 |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aaeaf40819087fa0db989813e02 |
completed | May 8, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_69fd8b5929c08190ae4596a23857ed06 |
completed | May 8, 2026, 7:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8beb5d608190b4825ccb0935f041 |
completed | May 8, 2026, 7:08 a.m. |
Created at: April 10, 2026, 1:21 a.m.