Triple
T2417160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Seonghwan |
E52331
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object |
Seonghwan
Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
|
E265429
|
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: Seonghwan | Statement: [Battle of Seonghwan, location, Seonghwan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seonghwan Context triple: [Battle of Seonghwan, location, Seonghwan]
-
A.
Jinwicheon
Jinwicheon is a river flowing through the city of Pyeongtaek in South Korea.
-
B.
Naong Hyegeun
Naong Hyegeun was a prominent Korean Buddhist monk and reformer of the Goryeo dynasty, known for revitalizing Seon (Zen) Buddhism and establishing important temples.
-
C.
Lee Hak-rae
Lee Hak-rae is a South Korean sports official best known for delivering the judges' oath at the 1988 Seoul Summer Olympics.
-
D.
Yong-il
Yong-il is a Korean masculine given name that can be shared by various individuals, including notable figures such as politicians and public officials.
-
E.
O Yeong-su
O Yeong-su is a veteran South Korean actor best known internationally for his acclaimed performance as the elderly contestant Oh Il-nam in the Netflix series "Squid Game."
- 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: Seonghwan Triple: [Battle of Seonghwan, location, Seonghwan]
Generated description
Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seonghwan Target entity description: Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
-
A.
Jinwicheon
Jinwicheon is a river flowing through the city of Pyeongtaek in South Korea.
-
B.
Naong Hyegeun
Naong Hyegeun was a prominent Korean Buddhist monk and reformer of the Goryeo dynasty, known for revitalizing Seon (Zen) Buddhism and establishing important temples.
-
C.
Lee Hak-rae
Lee Hak-rae is a South Korean sports official best known for delivering the judges' oath at the 1988 Seoul Summer Olympics.
-
D.
Yong-il
Yong-il is a Korean masculine given name that can be shared by various individuals, including notable figures such as politicians and public officials.
-
E.
O Yeong-su
O Yeong-su is a veteran South Korean actor best known internationally for his acclaimed performance as the elderly contestant Oh Il-nam in the Netflix series "Squid Game."
- 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94eafd481909eeff689e5bf5960 |
completed | March 7, 2026, 6:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf4dcf6c8190a51f26af7e7a9b9c |
completed | March 9, 2026, 12:38 p.m. |
| NEDg | Description generation | batch_69aec2b3291c8190966344cd20963660 |
completed | March 9, 2026, 12:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aec30f9ef481909b83f3cf9fd6e998 |
completed | March 9, 2026, 12:54 p.m. |
Created at: March 6, 2026, 9:42 p.m.