Triple
T8781032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibuya |
E208724
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Nakano |
E310221
|
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: Nakano | Statement: [Shibuya, borderedBy, Nakano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nakano Context triple: [Shibuya, borderedBy, Nakano]
-
A.
Nakano
chosen
Nakano is a special ward in Tokyo, Japan, known for its dense urban neighborhoods, anime and subculture shopping areas, and convenient access to central Tokyo.
-
B.
Nishi-Okano
Nishi-Okano is a notable neighborhood within Nishi Ward in the city of Yokohama, Japan.
-
C.
Kawaguchi
Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
-
D.
Murayama
Murayama is a Japanese surname borne by various notable individuals across fields such as politics, science, and the arts.
-
E.
Wakamatsu
Wakamatsu is a ward in the city of Kitakyushu, Japan, known historically as a port and industrial area on the northern coast of Kyushu.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f55b7b08190ab3e18cd634a144b |
completed | March 31, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d55585857c8190a4e4626a92197232 |
completed | April 7, 2026, 7:05 p.m. |
Created at: March 30, 2026, 6:42 p.m.