Triple
T7468733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wels |
E176447
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Chinju
Chinju (often spelled Jinju) is a city in South Gyeongsang Province, South Korea, known for its historic fortress, Namgang Yudeung (Lantern) Festival, and rich cultural heritage.
|
E671240
|
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: Chinju | Statement: [Wels, hasTwinTown, Chinju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chinju Context triple: [Wels, hasTwinTown, Chinju]
-
A.
Sokcho
Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
-
B.
Ungjin
Ungjin was an ancient city in the Korean kingdom of Baekje that served as one of its historical capitals and a key political and cultural center.
-
C.
Gwangyang
Gwangyang is an industrial port city in South Korea known for its major steelworks complex and scenic coastal and mountainous landscapes.
-
D.
Gangjin
Gangjin is a coastal county and town in South Jeolla Province, South Korea, known for its historic celadon pottery kilns and scenic rural landscapes.
-
E.
Mokpo
Mokpo is a coastal city in South Jeolla Province, South Korea, known as a regional transportation hub and gateway to numerous nearby islands.
- 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: Chinju Triple: [Wels, hasTwinTown, Chinju]
Generated description
Chinju (often spelled Jinju) is a city in South Gyeongsang Province, South Korea, known for its historic fortress, Namgang Yudeung (Lantern) Festival, and rich cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chinju Target entity description: Chinju (often spelled Jinju) is a city in South Gyeongsang Province, South Korea, known for its historic fortress, Namgang Yudeung (Lantern) Festival, and rich cultural heritage.
-
A.
Sokcho
Sokcho is a coastal city in northeastern South Korea known for its beaches, seafood, and proximity to Seoraksan National Park.
-
B.
Ungjin
Ungjin was an ancient city in the Korean kingdom of Baekje that served as one of its historical capitals and a key political and cultural center.
-
C.
Gwangyang
Gwangyang is an industrial port city in South Korea known for its major steelworks complex and scenic coastal and mountainous landscapes.
-
D.
Gangjin
Gangjin is a coastal county and town in South Jeolla Province, South Korea, known for its historic celadon pottery kilns and scenic rural landscapes.
-
E.
Mokpo
Mokpo is a coastal city in South Jeolla Province, South Korea, known as a regional transportation hub and gateway to numerous nearby islands.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3f6f23881908e3e80b0c7335a15 |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84eeaddb48190890b3e07967e12fa |
completed | March 28, 2026, 9:58 p.m. |
| NEDg | Description generation | batch_69c8509293788190887810c91e40e481 |
completed | March 28, 2026, 10:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8511ac76481909fd8a00626860199 |
completed | March 28, 2026, 10:07 p.m. |
Created at: March 27, 2026, 3:40 p.m.