Triple
T2671384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginkaku-ji |
E55753
|
entity |
| Predicate | hasBuilding |
P105
|
FINISHED |
| Object | Kannon-den |
E234489
|
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: Kannon-den | Statement: [Ginkaku-ji, hasBuilding, Kannon-den]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kannon-den Context triple: [Ginkaku-ji, hasBuilding, Kannon-den]
-
A.
Kannon
chosen
Kannon is the Japanese name for the bodhisattva of compassion, derived from the Buddhist deity Avalokiteshvara and widely venerated in Japan.
-
B.
Hacha-Kekan
Hacha-Kekan is a traditional cultural festival of the Karbi people that showcases their indigenous rituals, music, dance, and communal celebrations.
-
C.
Kawaiisu
Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
-
D.
Kono
Kono is a Japanese surname most prominently associated with politician Taro Kono, a leading figure in contemporary Japanese politics.
-
E.
Nakanamanga
Nakanamanga is an Oceanic Austronesian language spoken primarily on Efate Island and nearby areas in Vanuatu.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98e7d00819088398206fc7db477 |
completed | March 7, 2026, 7:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf54711881909936ecf850ff6e2e |
completed | March 10, 2026, 5:42 a.m. |
Created at: March 6, 2026, 9:54 p.m.