Triple
T12946507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinkansen |
E309780
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | bullet train |
E309780
|
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: bullet train | Statement: [Shinkansen, nickname, bullet train]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: bullet train Context triple: [Shinkansen, nickname, bullet train]
-
A.
Shinkansen
chosen
Shinkansen is Japan’s high-speed bullet train network, renowned for its punctuality, safety, and advanced rail technology.
-
B.
XPT train
The XPT train is a long-distance, high-speed diesel passenger train used in New South Wales, Australia, based on the British InterCity 125 design.
-
C.
High Speed Train
The High Speed Train is a British high-speed diesel-powered passenger train, best known for its long-distance intercity services and record-setting performance on the UK rail network.
-
D.
Sanyo Shinkansen
Sanyo Shinkansen is a high-speed railway line in Japan that connects Osaka with western Honshu cities such as Hiroshima and Fukuoka as part of the Shinkansen network.
-
E.
Shinonsen
Shinonsen is a town in northern Hyōgo Prefecture, Japan, known for its hot spring resorts and scenic coastal and mountainous landscapes.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e1b3694819098527dcea3cfed93 |
completed | April 10, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af75bc04819098d98c47fca48ac9 |
completed | May 3, 2026, 2:14 a.m. |
Created at: April 9, 2026, 5:43 p.m.