Triple
T13657410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 伊東祐亨 |
E326896
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object | 青山霊園 |
E75380
|
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: 青山霊園 | Statement: [伊東祐亨, burialPlace, 青山霊園]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 青山霊園 Context triple: [伊東祐亨, burialPlace, 青山霊園]
-
A.
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.
-
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.
Yokohama Foreign General Cemetery
Yokohama Foreign General Cemetery is a historic burial ground in Yokohama where many of the city’s early foreign residents and notable expatriates are interred.
-
D.
多磨霊園
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。
-
E.
Aoyama Cemetery, Tokyo
chosen
Aoyama Cemetery in Tokyo is a historic and prestigious public graveyard known for being the resting place of many prominent Japanese political and cultural figures.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc61d56e4819084ae3c16ecdf4a05 |
completed | April 12, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b06c5d081909d31b8a537c94edb |
completed | May 3, 2026, 5:51 p.m. |
Created at: April 9, 2026, 9:52 p.m.