Triple
T32424591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 三井寺 |
E828543
|
entity |
| Predicate | 主な建造物 |
P112855
|
FINISHED |
| Object |
新羅明神社
新羅明神社は、滋賀県大津市の天台寺門宗総本山・三井寺(園城寺)の境内にある、古くから新羅明神を祀る社で、寺と神社が共存する神仏習合の歴史を今に伝える神社です。
|
E2006028
|
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: 新羅明神社 | Statement: [三井寺, 主な建造物, 新羅明神社]
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: 新羅明神社 Triple: [三井寺, 主な建造物, 新羅明神社]
Generated description
新羅明神社は、滋賀県大津市の天台寺門宗総本山・三井寺(園城寺)の境内にある、古くから新羅明神を祀る社で、寺と神社が共存する神仏習合の歴史を今に伝える神社です。
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_69f3491b28bc8190b75cea7a507f337b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c286ac288190843dac21651babd0 |
completed | May 3, 2026, 3:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a344f28cc3c8190894ce0c64aca697d |
completed | June 18, 2026, 8:03 p.m. |
| NEDg | Description generation | batch_6a344ff6fd188190b5c585e81427a37b |
completed | June 18, 2026, 8:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3450d7fb488190b39c09e0761cb81c |
completed | June 18, 2026, 8:11 p.m. |
Created at: May 1, 2026, 12:54 a.m.