Triple
T20822794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JS Izumo |
E512619
|
entity |
| Predicate | builder |
P3143
|
FINISHED |
| Object | Japan Marine United |
—
|
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: Japan Marine United | Statement: [JS Izumo, builder, Japan Marine United]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Japan Marine United Context triple: [JS Izumo, builder, Japan Marine United]
-
A.
Japan Marine United
chosen
Japan Marine United is a major Japanese shipbuilding company known for constructing advanced naval vessels for the Japan Maritime Self-Defense Force and commercial ships for global markets.
-
B.
Osaka Marubiru
Osaka Marubiru is a prominent multi-purpose commercial building and shopping complex located in Osaka’s Umeda business district.
-
C.
Nisshin
Nisshin is a suburban city in central Japan known for its residential communities and proximity to Nagoya in Aichi Prefecture.
-
D.
Nippon Yusen Kaisha
Nippon Yusen Kaisha is one of Japan’s largest and oldest shipping and logistics companies, operating a global fleet for maritime transport and related services.
-
E.
Imabari Shipbuilding
Imabari Shipbuilding is a major Japanese shipbuilding company known for constructing large commercial vessels, including some of the world’s biggest container ships.
- 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2fb49148190bdad1b51e7dac43a |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.