Triple
T20166872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsuda |
E491844
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Kaisei |
—
|
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: Kaisei | Statement: [Matsuda, borderedBy, Kaisei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaisei Context triple: [Matsuda, borderedBy, Kaisei]
-
A.
Kaisei
chosen
Kaisei is a small town in Kanagawa Prefecture, Japan, known for its residential character and proximity to larger urban centers.
-
B.
Kaiseijo
Kaiseijo was a key early Meiji-era educational institution in Japan that helped modernize the country’s higher learning and laid the groundwork for the University of Tokyo.
-
C.
Gaifū Kaisei
Gaifū Kaisei is a famous woodblock print by Japanese ukiyo-e artist Katsushika Hokusai, depicting Mount Fuji under a clear morning sky with a red-tinged peak.
-
D.
Kudanshita
Kudanshita is a district and major subway station area in central Tokyo known for its proximity to the Imperial Palace, Yasukuni Shrine, and several universities and office buildings.
-
E.
Daiukku
Daiukku is an alternative name for Deioces, the legendary founder and first king of the Median Empire in ancient Iran.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66844e49081909b7e9ec2b65cc61d |
completed | April 20, 2026, 5:54 p.m. |
Created at: April 11, 2026, 11:35 p.m.