Triple
T13875434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōtō |
E333569
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Toyosu |
—
|
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: Toyosu | Statement: [Kōtō, contains, Toyosu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toyosu Context triple: [Kōtō, contains, Toyosu]
-
A.
Toyosu
chosen
Toyosu is a modern waterfront district in Tokyo best known for its large-scale urban redevelopment and the Toyosu Market, which replaced the historic Tsukiji fish market.
-
B.
Hayama
Hayama is a coastal town in Kanagawa Prefecture, Japan, known for its beaches, scenic views of Sagami Bay, and as a site of an Imperial Villa.
-
C.
Tsuruga
Tsuruga is a coastal city in Fukui Prefecture, Japan, known as a key port and transportation hub on the Sea of Japan side of Honshu.
-
D.
Sodegaura
Sodegaura is a coastal city in Chiba Prefecture, Japan, known for its industrial waterfront, proximity to Tokyo Bay, and role within the Keiyō industrial zone.
-
E.
Kamaishi
Kamaishi is a coastal city in northeastern Japan known for its historic iron and steel industry and as a venue for the 2019 Rugby World Cup.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0be556708190bbcf0b3583f677e3 |
completed | April 14, 2026, 9:41 a.m. |
Created at: April 9, 2026, 10:15 p.m.