Triple
T15561923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese cruiser Mikuma |
E371019
|
entity |
| Predicate | hullNumber |
P3152
|
FINISHED |
| Object | Mikuma |
E93464
|
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: Mikuma | Statement: [Japanese cruiser Mikuma, hullNumber, Mikuma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mikuma Context triple: [Japanese cruiser Mikuma, hullNumber, Mikuma]
-
A.
Mikuma
chosen
Mikuma was a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served in World War II and was sunk during the Battle of Midway.
-
B.
Machimura
Machimura is a Japanese surname most notably associated with Nobutaka Machimura, a prominent Liberal Democratic Party politician and former foreign minister of Japan.
-
C.
Mukawa
Mukawa is a coastal town in Hokkaido, Japan, known for its fishing industry and scenic natural surroundings.
-
D.
Moruya
Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
-
E.
Mankoya
Mankoya is a dialect of the Silozi language spoken by communities in parts of southwestern Zambia.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddb4c0c81909b3f4c75c91f7f3f |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff28d38a4819085bf051b566c17e7 |
completed | May 10, 2026, 2:50 a.m. |
Created at: April 10, 2026, 4:09 a.m.