Triple
T16537198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suginami |
E401722
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Mitaka |
—
|
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: Mitaka | Statement: [Suginami, borderedBy, Mitaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mitaka Context triple: [Suginami, borderedBy, Mitaka]
-
A.
Mitaka
chosen
Mitaka is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the Ghibli Museum.
-
B.
Tsuchiura
Tsuchiura is a city in Ibaraki Prefecture, Japan, known for its location on the shores of Lake Kasumigaura and its annual national fireworks competition.
-
C.
Wakatsuki
Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
-
D.
Hiranaka
Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
-
E.
Matsuda
Matsuda is a small town in Kanagawa Prefecture, Japan, known for its scenic views of Mount Fuji and seasonal flower festivals.
- 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.