Triple
T11826315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Buddhist Canon |
E281267
|
entity |
| Predicate | majorEdition |
P3094
|
FINISHED |
| Object | Kaibao Canon |
E703880
|
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: Kaibao Canon | Statement: [Chinese Buddhist Canon, majorEdition, Kaibao Canon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaibao Canon Context triple: [Chinese Buddhist Canon, majorEdition, Kaibao Canon]
-
A.
Kaibao
chosen
Kaibao was the era name marking the early reign of Emperor Taizu, founder of China’s Song dynasty.
-
B.
Kannon
Kannon is the Japanese name for the bodhisattva of compassion, derived from the Buddhist deity Avalokiteshvara and widely venerated in Japan.
-
C.
Happo-One
Happo-One is a major ski resort in Japan’s Northern Alps, renowned for its extensive slopes, deep powder, and role as a venue during the 1998 Nagano Winter Olympics.
-
D.
Shuji
Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
-
E.
Ōsu Kannon
Ōsu Kannon is a famous Buddhist temple in Nagoya, Japan, known for its large wooden statue of Kannon and its surrounding shopping arcade.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5ec3a148190bb184ba0d481b16a |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f132062b108190ad33656c386ee603 |
completed | April 28, 2026, 10:17 p.m. |
Created at: April 8, 2026, 9:43 p.m.