Triple
T21800463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 横浜たまプラーザキャンパス |
E538225
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | 横浜市 |
—
|
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: 横浜市 | Statement: [横浜たまプラーザキャンパス, locatedIn, 横浜市]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 横浜市 Context triple: [横浜たまプラーザキャンパス, locatedIn, 横浜市]
-
A.
Yokohama
chosen
Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
-
B.
Shinagawa City
Shinagawa City is a special ward in Tokyo, Japan, known as a major commercial and transportation hub with a mix of business districts and residential neighborhoods.
-
C.
Sagamihara
Sagamihara is a major city in Kanagawa Prefecture, Japan, known as a residential and industrial hub within the Greater Tokyo metropolitan area.
-
D.
Bunkyō City
Bunkyō City is a special ward in central Tokyo, Japan, known for its universities, historic temples, and quiet residential neighborhoods.
-
E.
Shibuya City
Shibuya City is a major commercial and entertainment district in central Tokyo, Japan, famous for its bustling scramble crossing, youth culture, and fashion scene.
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f077fede848190b8fe07941d6573d9 |
completed | April 28, 2026, 9:03 a.m. |
Created at: April 16, 2026, 6:53 p.m.