Triple
T16537206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suginami |
E401722
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Asagaya |
—
|
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: Asagaya | Statement: [Suginami, contains, Asagaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asagaya Context triple: [Suginami, contains, Asagaya]
-
A.
Asagaya
chosen
Asagaya is a residential and commercial neighborhood in Tokyo known for its traditional shopping streets, local festivals, and convenient access to central Tokyo.
-
B.
Kamitabashi
Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
-
C.
Toyonaka
Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
-
D.
Nagatacho
Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
-
E.
Komagome
Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34559ca948190a9eb810b9b3be079 |
completed | April 18, 2026, 8:48 a.m. |
Created at: April 10, 2026, 5:15 a.m.