Triple
T15158362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryūkōji |
E362139
|
entity |
| Predicate | hasStructure |
P35
|
FINISHED |
| Object | Daishidō |
E1135792
|
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: Daishidō | Statement: [Ryūkōji, hasStructure, Daishidō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daishidō Context triple: [Ryūkōji, hasStructure, Daishidō]
-
A.
Daishidō
chosen
Daishidō is a hall within the Ryōzenji temple complex in Japan, typically dedicated to the revered Buddhist monk Kōbō Daishi.
-
B.
Gaimushō
Gaimushō is Japan’s Ministry of Foreign Affairs, responsible for managing the country’s diplomatic relations and international policies.
-
C.
Daikoku
Daikoku is a prominent Japanese deity of wealth, agriculture, and household prosperity, often depicted with a mallet and rice bales and revered as one of the Seven Lucky Gods.
-
D.
Jūrakuji
Jūrakuji is a Buddhist temple in Japan best known as Temple 7 on the Shikoku 88-temple pilgrimage route.
-
E.
Shinto Taikyo
Shinto Taikyo is a Shinto religious sect in Japan that emphasizes traditional Shinto rituals and teachings within the broader framework of Sect Shinto.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060dd71881908ecc4a4f52d438a5 |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec88419108190860319a9bcab1eef |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:08 a.m.