Triple
T15378876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omotesandō |
E367745
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Aoyama area |
E265636
|
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: Aoyama area | Statement: [Omotesandō, partOf, Aoyama area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aoyama area Context triple: [Omotesandō, partOf, Aoyama area]
-
A.
Aoyama area
chosen
The Aoyama area is an upscale Tokyo neighborhood known for its fashionable boutiques, contemporary architecture, and trendy cafes and galleries.
-
B.
Yokokawa area
The Yokokawa area is one of the three main temple precincts of Enryaku-ji on Mount Hiei, known for its secluded, forested setting and historic Buddhist halls.
-
C.
Aoyama district
Aoyama district is an upscale neighborhood in central Tokyo known for its fashionable boutiques, trendy cafes, art galleries, and modern architecture.
-
D.
Nippori area
Nippori area is a neighborhood in Tokyo known for its traditional shitamachi atmosphere, fabric and textile district, and proximity to major rail connections.
-
E.
Tsuruhashi area
The Tsuruhashi area is a bustling Osaka neighborhood famous for its large Koreatown, vibrant markets, and numerous yakiniku and Korean restaurants.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e6044488190b0499db109f7f821 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff364d82c48190b116528b5c00e918 |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:19 a.m.