Triple
T11266709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shitennoji Temple |
E266704
|
entity |
| Predicate | hasMainHall |
P6080
|
FINISHED |
| Object | Kondo |
E483064
|
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: Kondo | Statement: [Shitennoji Temple, hasMainHall, Kondo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kondo Context triple: [Shitennoji Temple, hasMainHall, Kondo]
-
A.
Kondo
chosen
Kondo is the main hall of Yakushi-ji Temple in Nara, Japan, renowned for enshrining important Buddhist images and serving as the temple’s central worship space.
-
B.
Takaichi
Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
-
C.
Norikura
Norikura is a ski resort area in Japan’s Hakuba Valley, known for its scenic alpine terrain and winter sports opportunities.
-
D.
Shuji
Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
-
E.
Warekena
The Warekena are an Indigenous people of the Amazon region, primarily living along rivers in Brazil and Venezuela, known for their distinct Arawakan language and traditional riverine lifestyle.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94e5e3c8190a31995d55d20d7ed |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ccd52c20819093e03bba2fd359b7 |
completed | April 19, 2026, 12:38 p.m. |
Created at: April 8, 2026, 9:31 p.m.