Triple
T31631305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 三軒茶屋駅 |
E807172
|
entity |
| Predicate | 路線 |
P848
|
FINISHED |
| Object |
東急田園都市線
東急田園都市線は、東京都渋谷区の渋谷駅から神奈川県大和市の中央林間駅までを結び、都心と郊外のベッドタウンを結ぶ主要な通勤路線として機能する東急電鉄の鉄道路線である。
|
E1971330
|
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: 東急田園都市線 | Statement: [三軒茶屋駅, 路線, 東急田園都市線]
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: 東急田園都市線 Triple: [三軒茶屋駅, 路線, 東急田園都市線]
Generated description
東急田園都市線は、東京都渋谷区の渋谷駅から神奈川県大和市の中央林間駅までを結び、都心と郊外のベッドタウンを結ぶ主要な通勤路線として機能する東急電鉄の鉄道路線である。
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_69f348d892948190915f8facacb9568c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a8e5799c8190900640d78b1c5990 |
completed | May 3, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2b79d4a3248190aba0de6d36e4c5db |
completed | June 12, 2026, 3:15 a.m. |
| NEDg | Description generation | batch_6a2b7a517e8c819090df69ab80325863 |
completed | June 12, 2026, 3:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a2b7b197efc8190ae82e4badb5745ac |
completed | June 12, 2026, 3:20 a.m. |
Created at: April 30, 2026, 10:45 p.m.