Triple
T11803978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Togoshi Ginza Shopping Street |
E280697
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Togoshi |
E496311
|
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: Togoshi | Statement: [Togoshi Ginza Shopping Street, locatedIn, Togoshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Togoshi Context triple: [Togoshi Ginza Shopping Street, locatedIn, Togoshi]
-
A.
Togoshi
chosen
Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
-
B.
Tōgane
Tōgane is a coastal city in Chiba Prefecture, Japan, known for its proximity to the long sandy stretch of Kujūkuri Beach along the Pacific Ocean.
-
C.
Takarano
Takarano is a small settlement on the atoll of Tabiteuea in the island nation of Kiribati, located in the central Pacific Ocean.
-
D.
Takarano
Takarano is a village located on the atoll of Abaiang in the island nation of Kiribati.
-
E.
Yonashiro
Yonashiro was a former town in Okinawa Prefecture, Japan, that later became part of the city of Uruma through municipal merger.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5a5a2048190b68027f622366079 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe46175b88190ae687073ddaa3d22 |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 8, 2026, 9:42 p.m.