Triple
T16079413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanda River |
E390064
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Suginami ward |
—
|
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: Suginami ward | Statement: [Kanda River, flowsThrough, Suginami ward]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suginami ward Context triple: [Kanda River, flowsThrough, Suginami ward]
-
A.
Suginami Ward
chosen
Suginami Ward is one of Tokyo’s 23 special wards, known as a largely residential area with numerous parks, local shopping streets, and a strong community atmosphere.
-
B.
Toshima ward
Toshima ward is a special ward in Tokyo, Japan, known for its major commercial and entertainment hub Ikebukuro and its dense urban residential neighborhoods.
-
C.
Bunkyō ward
Bunkyō ward is a central Tokyo district known for its universities, cultural institutions, and quiet residential neighborhoods.
-
D.
Nakano Ward
Nakano Ward is a special ward in western Tokyo, Japan, known for its dense residential neighborhoods, shopping streets, and subculture hubs like Nakano Broadway.
-
E.
Minami Ward
Minami Ward is one of the administrative wards of Kumamoto City in Japan, encompassing a mix of residential, commercial, and rural areas.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18448bebc8190b0e84b1da097bf8b |
completed | April 17, 2026, 12:52 a.m. |
Created at: April 10, 2026, 4:57 a.m.