Triple
T15336076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bunkyō City |
E366668
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Arakawa |
—
|
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: Arakawa | Statement: [Bunkyō City, borderedBy, Arakawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arakawa Context triple: [Bunkyō City, borderedBy, Arakawa]
-
A.
Arakawa
chosen
Arakawa is a special ward in Tokyo, Japan, known for its mix of traditional residential neighborhoods and industrial areas along the Arakawa River.
-
B.
Urakawa
Urakawa is a coastal town in Hokkaido, Japan, known for its horse breeding industry and scenic Pacific shoreline.
-
C.
Aikawa
Aikawa was a former town in Niigata Prefecture, Japan, known historically for its role in the Sado gold and silver mining region before being merged into the city of Sado.
-
D.
Aikawa
Aikawa is a town in Kanagawa Prefecture, Japan, known for its residential communities and proximity to the industrial and commercial city of Atsugi.
-
E.
Yamakawa
Yamakawa is a Japanese surname historically associated with notable Meiji-era figures, including the influential educator and social reformer Ōyama Sutematsu.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e03c5f081908e4d14dbdbc7f7a6 |
completed | April 16, 2026, 1:40 a.m. |
Created at: April 10, 2026, 3:17 a.m.