Triple
T9191301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 黒川紀章 |
E220593
|
entity |
| Predicate | 出生地 |
P1
|
FINISHED |
| Object | 愛知県名古屋市 |
E410777
|
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: 愛知県名古屋市 | Statement: [黒川紀章, 出生地, 愛知県名古屋市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 愛知県名古屋市 Context triple: [黒川紀章, 出生地, 愛知県名古屋市]
-
A.
愛知県豊橋市
愛知県豊橋市は、愛知県東部に位置する中核市で、工業と農業がともに盛んで交通の要衝としても知られる都市です。
-
B.
Nagoya, Aichi, Japan
chosen
Nagoya, Aichi, Japan is a major industrial and commercial city in central Japan, known as a key manufacturing hub—especially for the automotive industry—and the largest city in the Chūbu region.
-
C.
Nagoya
Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
-
D.
Shizuoka City, Japan
Shizuoka City, Japan is a coastal city in central Honshu known for its views of Mount Fuji, green tea production, and role as a regional economic and cultural center.
-
E.
Chikusa-ku, Nagoya
Chikusa-ku, Nagoya is a ward in the city of Nagoya, Japan, known for its academic institutions, residential neighborhoods, and cultural facilities.
- 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd5bf25c081909e651b67ef8ecc33 |
completed | April 1, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c272f508190aade1769c88cf16d |
completed | April 4, 2026, 12:32 a.m. |
Created at: March 30, 2026, 7:24 p.m.