Triple
T11854694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirokane |
E282003
|
entity |
| Predicate | nearTo |
P350
|
FINISHED |
| Object | Shirokanedai |
E348226
|
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: Shirokanedai | Statement: [Shirokane, nearTo, Shirokanedai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shirokanedai Context triple: [Shirokane, nearTo, Shirokanedai]
-
A.
Komagome
Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
-
B.
Shiodome
Shiodome is a modern high-rise business and commercial district in Tokyo, Japan, known for housing major corporate headquarters, upscale hotels, and shopping complexes.
-
C.
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.
-
D.
Toyosu
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.
-
E.
Shirokanedai district
chosen
Shirokanedai district is an upscale residential and educational area in Minato, Tokyo, known for its quiet streets, embassies, universities, and proximity to parks and museums.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a697f4108190af984932d2118472 |
completed | April 10, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01232149f88190b385fca6a7588d7b |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:43 p.m.