Triple
T1385317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daikanyama |
E29830
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Ebisu |
E29485
|
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: Ebisu | Statement: [Daikanyama, near, Ebisu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ebisu Context triple: [Daikanyama, near, Ebisu]
-
A.
Ebisu
chosen
Ebisu is a fashionable Tokyo neighborhood known for its upscale dining, craft beer scene, and convenient access via Ebisu Station near Shibuya.
-
B.
Akita
Akita is a city in Japan’s Tōhoku region, serving as the capital of Akita Prefecture and known for its port, rice production, and traditional festivals.
-
C.
Ōiso
Ōiso is a coastal town in Kanagawa Prefecture, Japan, known as a historic seaside resort and former political retreat.
-
D.
Kawaiisu
Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
-
E.
Sukki
Sukki is one of the four snowman mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c339f3d481909c04b14129899945 |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd48e046c8190bc4820d6c4ce907d |
completed | March 8, 2026, 1:44 a.m. |
Created at: March 1, 2026, 7:59 p.m.