Triple
T16407504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota Tsusho Corporation |
E398472
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object | Nagoya City |
—
|
NE NERFINISHED |
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: Nagoya City | Statement: [Toyota Tsusho Corporation, headquartersLocation, Nagoya City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagoya City Context triple: [Toyota Tsusho Corporation, headquartersLocation, Nagoya City]
-
A.
Nagoya
chosen
Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
-
B.
Nankoku City
Nankoku City is a regional city on the island of Shikoku in Japan, known for its agricultural production and proximity to the city of Kōchi.
-
C.
Yokohama
Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
-
D.
Osaka
Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
-
E.
Osaki City
Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d36b808190b6b8c412ae0d2faa |
completed | April 18, 2026, 6:42 a.m. |
Created at: April 10, 2026, 5:09 a.m.