Triple
T17240600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirinashi River |
E418484
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Naniwa-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: Naniwa-ku | Statement: [Shirinashi River, flowsThrough, Naniwa-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naniwa-ku Context triple: [Shirinashi River, flowsThrough, Naniwa-ku]
-
A.
Naniwa-ku
chosen
Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
-
B.
Nishinari-ku
Nishinari-ku is a ward in Osaka, Japan, known for its dense urban environment, working-class neighborhoods, and historically being one of the city's poorest districts.
-
C.
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.
-
D.
Izumi-ku
Izumi-ku is a northern residential and commercial ward of Sendai in Miyagi Prefecture, Japan, known for its suburban neighborhoods and shopping centers.
-
E.
Taihaku-ku
Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e1f385c8190ae44e702923b6f66 |
completed | April 19, 2026, 1:21 a.m. |
Created at: April 10, 2026, 5:39 a.m.