Triple
T9888109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumida, Tokyo, Japan |
E181386
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Kinshichō |
E211200
|
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: Kinshichō | Statement: [Sumida, Tokyo, Japan, hasDistrict, Kinshichō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinshichō Context triple: [Sumida, Tokyo, Japan, hasDistrict, Kinshichō]
-
A.
Kinshichō
chosen
Kinshichō is a major commercial and entertainment district in eastern Tokyo known for its large shopping complexes, nightlife, and convenient rail connections.
-
B.
Keiyo
Keiyo is a Southern Nilotic language spoken primarily by the Keiyo people of Kenya’s Rift Valley region.
-
C.
Kuneē
Kuneē is the mythological helmet worn by Hades that grants its wearer invisibility in Greek mythology.
-
D.
Kitasenju
Kitasenju is a major commercial and transportation hub in Adachi, Tokyo, known for its busy train station, shopping complexes, and urban downtown atmosphere.
-
E.
Kantokuen
Kantokuen was an Imperial Japanese Army war plan developed in 1941 for a large-scale invasion of the Soviet Far East from Manchuria.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4592db881909b134834dde614d8 |
completed | April 2, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb0314108190b35906592a11727e |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:39 p.m.