Triple
T37864781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 嵐電(京福電気鉄道嵐山本線) |
E944439
|
entity |
| Predicate | 代表的駅 |
P189299
|
FINISHED |
| Object |
有栖川駅
有栖川駅は、京都市右京区に位置し、観光地・嵐山エリアへのアクセス拠点として利用される京福電気鉄道嵐山本線の駅である。
|
E2245985
|
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: 有栖川駅 | Statement: [嵐電(京福電気鉄道嵐山本線), 代表的駅, 有栖川駅]
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: 有栖川駅 Triple: [嵐電(京福電気鉄道嵐山本線), 代表的駅, 有栖川駅]
Generated description
有栖川駅は、京都市右京区に位置し、観光地・嵐山エリアへのアクセス拠点として利用される京福電気鉄道嵐山本線の駅である。
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_69f76eee2f9c8190b1272aa2ee55ebf5 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbd1ac9e88190833f43d4d774ada8 |
completed | May 6, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a410422d2808190b97cc5270f4aa09d |
completed | June 28, 2026, 11:23 a.m. |
| NEDg | Description generation | batch_6a4104af9ac88190a7ffe368c46f0f8d |
completed | June 28, 2026, 11:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41052129a08190a8e4d598dcd259b2 |
completed | June 28, 2026, 11:27 a.m. |
Created at: May 3, 2026, 4:19 p.m.