Triple
T22324370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 愛知県宝飯郡御津町 |
E551864
|
entity |
| Predicate | hasSuccessor |
P78
|
FINISHED |
| Object | 豊川市 |
—
|
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: 豊川市 | Statement: [愛知県宝飯郡御津町, hasSuccessor, 豊川市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 豊川市 Context triple: [愛知県宝飯郡御津町, hasSuccessor, 豊川市]
-
A.
豊川市
chosen
豊川市 is a city in eastern Aichi Prefecture, Japan, known for Toyokawa Inari Shrine and its mix of industrial activity and rich historical culture.
-
B.
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。
-
C.
Yoshinogawa City
Yoshinogawa City is a municipality in eastern Shikoku, Japan, known for its rural landscapes, historical sites, and proximity to the Yoshino River in Tokushima Prefecture.
-
D.
Kakegawa City
Kakegawa City is a regional city in central Japan known for its historic Kakegawa Castle and high-quality green tea production.
-
E.
Tagawa City
Tagawa City is a small inland municipality in central Fukuoka Prefecture, Japan, historically known as a coal-mining town and now a local commercial and cultural center.
- 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_69e11e482f788190b78d1588fc26d606 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15767425481909547bfe294fe06de |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:42 p.m.