Triple
T16814305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daikanyama Station |
E408700
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Daikanyama |
—
|
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: Daikanyama | Statement: [Daikanyama Station, locatedIn, Daikanyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daikanyama Context triple: [Daikanyama Station, locatedIn, Daikanyama]
-
A.
Daikanyama
chosen
Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
-
B.
Fukaya
Fukaya is a city in northern Saitama Prefecture, Japan, known historically as a post town and for its agricultural produce, particularly green onions.
-
C.
Fujinomiya
Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
-
D.
Okachimachi
Okachimachi is a bustling commercial and shopping district in Tokyo known for its discount stores, jewelry shops, and proximity to Ueno.
-
E.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b2e01fb8819081cf2c08f29448da |
completed | April 18, 2026, 4:35 p.m. |
Created at: April 10, 2026, 5:23 a.m.