Triple
T21927352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya Station |
E541474
|
entity |
| Predicate | servesWard |
P42362
|
FINISHED |
| Object | Nada-ku |
—
|
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: Nada-ku | Statement: [Maya Station, servesWard, Nada-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nada-ku Context triple: [Maya Station, servesWard, Nada-ku]
-
A.
Nada-ku
chosen
Nada-ku is a ward of Kobe in Japan’s Hyōgo Prefecture, known for its sake breweries, residential neighborhoods, and proximity to Mount Rokko.
-
B.
Naka-ku
Naka-ku is a central ward of Yokohama, Japan, known for its historic port area, Chinatown, and major commercial and entertainment districts.
-
C.
Nonoichi
Nonoichi is a city in Ishikawa Prefecture, Japan, known for its residential character and proximity to the regional hub of Kanazawa.
-
D.
Nakadori
Nakadori is the central inland region of Fukushima Prefecture in Japan, known for its transportation corridors, agriculture, and major cities such as Fukushima and Kōriyama.
-
E.
Kawachinagano
Kawachinagano is a city in southern Osaka Prefecture, Japan, known for its suburban residential areas, historical temples, and access to the surrounding mountainous countryside.
- 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_69e0c47d74488190a15119108794a307 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f123fc188481909c74fd5f1bd52258 |
completed | April 28, 2026, 9:17 p.m. |
Created at: April 16, 2026, 7:46 p.m.