Triple
T26933437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 대웅전 |
E678297
|
entity |
| Predicate | hasAssociatedStructure |
P2830
|
FINISHED |
| Object |
삼층석탑
삼층석탑은 한국 사찰 경내에 세워진 전형적인 석조 탑으로, 불교 신앙의 상징이자 미적·역사적 가치를 지닌 문화재이다.
|
E172729
|
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: 삼층석탑 | Statement: [대웅전, hasAssociatedStructure, 삼층석탑]
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: 삼층석탑 Triple: [대웅전, hasAssociatedStructure, 삼층석탑]
Generated description
삼층석탑은 한국 사찰 경내에 세워진 전형적인 석조 탑으로, 불교 신앙의 상징이자 미적·역사적 가치를 지닌 문화재이다.
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_69eeeb4cac908190a45956c2993d1cc2 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6204c2ef88190b7a4d6e0cc0e1127 |
completed | May 2, 2026, 4:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a121ec0df5c8190bdeafd951fe28348 |
completed | May 23, 2026, 9:40 p.m. |
| NEDg | Description generation | batch_6a1222ca264881909aa8fde0c811d9e0 |
completed | May 23, 2026, 9:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a122380eb708190a61dec3552516dd4 |
completed | May 23, 2026, 10 p.m. |
Created at: April 27, 2026, 6:14 a.m.