Triple
T29111848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeolla Line |
E736929
|
entity |
| Predicate | hasNameInKorean |
P17869
|
FINISHED |
| Object |
전라선
전라선은 대한민국 전라 지역을 남북으로 잇는 주요 철도 노선이다.
|
E1850052
|
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: 전라선 | Statement: [Jeolla Line, hasNameInKorean, 전라선]
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: 전라선 Triple: [Jeolla Line, hasNameInKorean, 전라선]
Generated description
전라선은 대한민국 전라 지역을 남북으로 잇는 주요 철도 노선이다.
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_69f077ed54e08190bb02a744e8121a66 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f661ed89f08190a52d68a08a0be6bb |
completed | May 2, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2537c36e5881909b2c42d92c86dbcc |
completed | June 7, 2026, 9:20 a.m. |
| NEDg | Description generation | batch_6a253c0a7d50819093cb8a95d0cfeb5d |
completed | June 7, 2026, 9:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a253fe575c48190834250931b48111c |
completed | June 7, 2026, 9:54 a.m. |
Created at: April 28, 2026, 11:19 a.m.