Triple
T14724599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Series E7 Shinkansen |
E345904
|
entity |
| Predicate | usedOnService |
P2367
|
FINISHED |
| Object | Kagayaki |
E719680
|
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: Kagayaki | Statement: [Series E7 Shinkansen, usedOnService, Kagayaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kagayaki Context triple: [Series E7 Shinkansen, usedOnService, Kagayaki]
-
A.
Kagayaki
chosen
Kagayaki is the fastest limited-stop train service operating on Japan’s Hokuriku Shinkansen line between Tokyo and the Hokuriku region.
-
B.
Kisogawa
Kisogawa is the Japanese name for the Kiso River, a major river in central Honshu known for its scenic valleys and historical importance.
-
C.
Kamogawa
Kamogawa is a coastal city in Chiba Prefecture, Japan, known for its beaches, fishing industry, and the popular Kamogawa Sea World aquarium.
-
D.
Kamogawa
Kamogawa is a prominent river running through Kyoto, Japan, known for its scenic banks, cultural significance, and popular walking paths.
-
E.
Chikuma
Chikuma was a Japanese Imperial Navy heavy cruiser that served prominently in World War II, including major Pacific naval battles.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec25e9a14819081fa06fc601f295d |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2ce36ce08190930e791e2837d1a5 |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 1:29 a.m.