Triple
T30700960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 온천장역 |
E781608
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
부산광역시 동래구
부산광역시 동래구는 부산 동부에 위치한 행정구로, 온천과 역사 유적, 주거·상업 지역이 조화를 이루는 도심 지역이다.
|
E1926759
|
NE FINISHED |
How this triple was built (2 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: 부산광역시 동래구 | Statement: [온천장역, locatedIn, 부산광역시 동래구]
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: 부산광역시 동래구 Triple: [온천장역, locatedIn, 부산광역시 동래구]
Generated description
부산광역시 동래구는 부산 동부에 위치한 행정구로, 온천과 역사 유적, 주거·상업 지역이 조화를 이루는 도심 지역이다.
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_69f224ab24e08190991d6edb6df58e8b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68bde6fac8190a20ba82428e655ab |
completed | May 2, 2026, 11:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a28711844408190946b2d573fe6440e |
completed | June 9, 2026, 8:01 p.m. |
| NEDg | Description generation | batch_6a287689fc648190a3ccf1b5c94a40ad |
completed | June 9, 2026, 8:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a28770182548190b06963ca19108cb8 |
completed | June 9, 2026, 8:26 p.m. |
Created at: April 29, 2026, 8:34 p.m.