Triple
T21716741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kagerō-class destroyer |
E536049
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Hagikaze |
—
|
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: Hagikaze | Statement: [Kagerō-class destroyer, hasPart, Hagikaze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hagikaze Context triple: [Kagerō-class destroyer, hasPart, Hagikaze]
-
A.
Hagikaze
chosen
Hagikaze was an Imperial Japanese Navy destroyer that served in World War II and was sunk during the Pacific War.
-
B.
Matsukaze
Matsukaze is a classic Noh play, traditionally attributed to Zeami, that poignantly depicts the lingering spirits of two salt-making sisters yearning for their lost lover.
-
C.
Katsuragi
Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
-
D.
Katsuragi
Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
-
E.
Eiryaku
Eiryaku was a Japanese era name (nengō) of the late Heian period, used during the reign of Emperor Go-Shirakawa.
- 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efd96ab4c88190b76f4a6b7c855039 |
completed | April 27, 2026, 9:47 p.m. |
Created at: April 16, 2026, 6:47 p.m.