Triple
T16239514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omotesando Station |
E394203
|
entity |
| Predicate | locatedInArea |
P40
|
FINISHED |
| Object | Aoyama |
—
|
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: Aoyama | Statement: [Omotesando Station, locatedInArea, Aoyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aoyama Context triple: [Omotesando Station, locatedInArea, Aoyama]
-
A.
Aoyama
chosen
Aoyama is an upscale district in Tokyo known for its high-end fashion boutiques, modern architecture, and trendy cafes and galleries.
-
B.
Oiyama
Oiyama is the climactic final race of the Hakata Gion Yamakasa festival in Fukuoka, where teams dash through the streets carrying elaborately decorated floats.
-
C.
Ōyama
Ōyama is a Japanese surname borne by various notable figures in Japan’s military, political, and cultural history.
-
D.
Oyama
Oyama is a small genus of flowering plants in the magnolia family, known for its ornamental, magnolia-like shrubs or small trees.
-
E.
Oyama
Oyama is a city in Tochigi Prefecture, Japan, known as a key commercial and transportation hub within the northern Kantō 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2455d5270819090171d4207223a28 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:04 a.m.