Triple
T13531730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spiral |
E323148
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Aoyama |
E190766
|
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 | Statement: [Spiral, district, Aoyama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aoyama Context triple: [Spiral, district, 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.
Yoiyama
Yoiyama is the lively evening street festival held before the main Gion Matsuri parade in Kyoto, featuring illuminated festival floats, food stalls, and traditional music.
-
E.
Iruma
Iruma is a city in Saitama Prefecture, Japan, known for its residential suburbs, Sayama Hills greenery, and tea cultivation.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafbb34548190a6b44faa48125cd4 |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b2e59e88190b58fdf9d9643aef9 |
completed | May 9, 2026, 10:23 a.m. |
Created at: April 9, 2026, 9:44 p.m.