Triple
T19390401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Great Temples of Nara |
E485049
|
entity |
| Predicate | transliteration |
P2508
|
FINISHED |
| Object | 南都七大寺 |
—
|
NE NERFINISHED |
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: 南都七大寺 | Statement: [Seven Great Temples of Nara, transliteration, 南都七大寺]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 南都七大寺 Context triple: [Seven Great Temples of Nara, transliteration, 南都七大寺]
-
A.
南都七大寺
chosen
南都七大寺 is the collective name for the seven great ancient Buddhist temples of Nara that played a central role in Japan’s religious and political life during the Nara period.
-
B.
善通寺
善通寺 is a historic Shingon Buddhist temple in Kagawa Prefecture, Japan, renowned as the birthplace and one of the principal pilgrimage sites associated with the monk Kūkai (Kōbō Daishi).
-
C.
归元禅寺
归元禅寺是一座位于湖北省武汉市汉阳区、以古朴建筑和众多佛像而闻名的历史悠久佛教寺院。
-
D.
白马寺
白马寺是位于中国河南省洛阳市、被誉为中国第一古刹的著名佛教寺院。
-
E.
三井寺
三井寺は、滋賀県大津市にある天台寺門宗の総本山で、琵琶湖近くに位置する歴史ある古刹です。
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b44b70c81908e2f0deeabe4360f |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.