Triple
T13875430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōtō |
E333569
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Sumida |
E34202
|
NE FINISHED |
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: Sumida | Statement: [Kōtō, borders, Sumida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sumida Context triple: [Kōtō, borders, Sumida]
-
A.
Sumida
chosen
Sumida is a special ward in Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional shitamachi neighborhoods.
-
B.
Nihonbashi River
The Nihonbashi River is a historic urban waterway in central Tokyo that has long served as an important commercial and transportation artery for the city.
-
C.
Sumida River
The Sumida River is a historically significant river flowing through central Tokyo, known for its scenic bridges, cherry blossoms, and cultural prominence in Japanese art and literature.
-
D.
Shibuya River
The Shibuya River is a small urban waterway in Tokyo that runs largely underground through the Shibuya district before joining the Meguro River.
-
E.
Meguro River
The Meguro River is a well-known urban river in Tokyo, Japan, famous for its picturesque cherry blossom-lined banks that attract many visitors during spring.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0be556708190bbcf0b3583f677e3 |
completed | April 14, 2026, 9:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce6df2ac819089024b9ede7b205f |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.