Triple
T16700202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 片山哲 |
E405823
|
entity |
| Predicate | 埋葬地 |
P196
|
FINISHED |
| Object | 多磨霊園（推定） |
E535214
|
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: 多磨霊園（推定） | Statement: [片山哲, 埋葬地, 多磨霊園（推定）]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 多磨霊園（推定） Context triple: [片山哲, 埋葬地, 多磨霊園（推定）]
-
A.
多磨霊園
chosen
多磨霊園は、東京都府中市と小金井市にまたがる日本初の公営火葬場併設型の大規模霊園で、多くの著名人が埋葬されていることで知られる墓地公園である。
-
B.
Kaze-no-Oka Crematorium
Kaze-no-Oka Crematorium is a contemplative, minimalist cremation complex in Japan designed by architect Fumihiko Maki, noted for its serene integration with the surrounding landscape.
-
C.
Zoshigaya Cemetery
Zoshigaya Cemetery is a historic public graveyard in Tokyo known for its tranquil, park-like setting and the graves of many notable Japanese cultural and political figures.
-
D.
霊山寺
霊山寺（りょうぜんじ）は、徳島県鳴門市にある四国八十八箇所霊場の第一番札所として知られる真言宗の寺院です。
-
E.
Okunoin cemetery
Okunoin cemetery is Japan’s largest and most sacred graveyard on Mount Koya, renowned as a major Shingon Buddhist pilgrimage site and the resting place of the monk Kobo Daishi.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e383300d108190911e3cba8e07f2dd |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00919ee61c81909928dd26270e9614 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.