Triple
T1244429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mamoru Shigemitsu |
E26731
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Tokyo, Japan |
E5560
|
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: Tokyo, Japan | Statement: [Mamoru Shigemitsu, placeOfDeath, Tokyo, Japan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tokyo, Japan Context triple: [Mamoru Shigemitsu, placeOfDeath, Tokyo, Japan]
-
A.
Tokyo
chosen
Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
-
B.
Nerima, Tokyo
Nerima, Tokyo is a residential special ward in northwestern Tokyo known for its suburban character, parks, and role as a hub for anime production studios.
-
C.
Yokohama
Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
-
D.
Toshima, Tokyo
Toshima, Tokyo is a special ward in northwestern Tokyo known for its major commercial and entertainment hub Ikebukuro and its mix of residential, educational, and cultural institutions.
-
E.
Chiyoda, Tokyo, Japan
Chiyoda is a central special ward of Tokyo that serves as Japan’s political and administrative heart, housing the Imperial Palace, the National Diet, and many government institutions.
- 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf636e208190a4d56806db61916c |
completed | March 1, 2026, 10:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae650fa53c8190a6db9d10c97f9850 |
completed | March 9, 2026, 6:13 a.m. |
Created at: March 1, 2026, 7:47 p.m.