Triple
T13951127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawasaki, Kanagawa |
E335525
|
entity |
| Predicate | hasWard |
P14475
|
FINISHED |
| Object | Saiwai-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: Saiwai-ku | Statement: [Kawasaki, Kanagawa, hasWard, Saiwai-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saiwai-ku Context triple: [Kawasaki, Kanagawa, hasWard, Saiwai-ku]
-
A.
Saiwai-ku
chosen
Saiwai-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known as an urban residential and commercial area within the Greater Tokyo metropolitan region.
-
B.
Wakabayashi-ku
Wakabayashi-ku is one of the administrative wards of Sendai, Japan, encompassing residential, commercial, and coastal areas in the eastern part of the city.
-
C.
Iwatsuki-ku
Iwatsuki-ku is a ward of Saitama City in Saitama Prefecture, Japan, known historically for its traditional doll-making industry.
-
D.
Nakahara-ku
Nakahara-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known as a residential and commercial area within the Greater Tokyo metropolitan region.
-
E.
Higashi-ku
Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e131c608190b4ffdbada24a3208 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 9, 2026, 10:17 p.m.