Triple
T13012431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nezu |
E322452
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Yanaka |
—
|
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: Yanaka | Statement: [Nezu, adjacentTo, Yanaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yanaka Context triple: [Nezu, adjacentTo, Yanaka]
-
A.
Yanaka
chosen
Yanaka is a traditional, temple-filled neighborhood in Tokyo known for its preserved old-town atmosphere, narrow lanes, and historic cemetery.
-
B.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
C.
Komagome
Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
-
D.
Shin-Okubo
Shin-Okubo is a Tokyo neighborhood best known for its vibrant Koreatown, dense cluster of Korean restaurants and shops, and multicultural atmosphere near Shinjuku.
-
E.
Osawa
Osawa is a Japanese surname and place name that serves as an alternative spelling of "Ozawa."
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecbb8f4819094d55eb07cb5ad97 |
completed | April 10, 2026, 10:50 p.m. |
Created at: April 9, 2026, 8:49 p.m.