Triple
T18068252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawasaki-ku |
E432349
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kawasaki 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: Kawasaki City | Statement: [Kawasaki-ku, locatedIn, Kawasaki City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kawasaki City Context triple: [Kawasaki-ku, locatedIn, Kawasaki City]
-
A.
Kawasaki City
chosen
Kawasaki City is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along Tokyo Bay.
-
B.
Osaki City
Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
-
C.
Miyazaki City
Miyazaki City is a coastal city in southeastern Kyushu, Japan, known for its mild climate, beaches, and role as an administrative and cultural center of the region.
-
D.
Kitakyushu
Kitakyushu is a major industrial and port city located in Fukuoka Prefecture on Japan’s Kyushu island.
-
E.
Yokkaichi
Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4cceb020081909329492591e7b1f2 |
completed | April 19, 2026, 12:39 p.m. |
Created at: April 10, 2026, 10:26 a.m.