Triple
T29634889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George |
E755683
|
entity |
| Predicate | hasJapaneseDesignation |
P28734
|
FINISHED |
| Object | Kawanishi N1K1-J Shiden |
—
|
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: Kawanishi N1K1-J Shiden | Statement: [George, hasJapaneseDesignation, Kawanishi N1K1-J Shiden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJapaneseDesignation Context triple: [George, hasJapaneseDesignation, Kawanishi N1K1-J Shiden]
-
A.
JapaneseDesignation
Indicates that one entity is formally designated, named, or classified in the Japanese language or by a Japanese authority.
-
B.
hasNameInJapanese
chosen
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
C.
hasOfficialNameInJapanese
Indicates that an entity has an official, formally recognized name expressed in the Japanese language.
-
D.
hasJapaneseSurname
Indicates that the person or entity possesses a surname that is of Japanese origin or is commonly used in Japanese naming conventions.
-
E.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
- F. None of above.
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_69f0ef88fbe081908f0ad90c1c413f1c |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f66e68f5588190b41a2060d3aea12f |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:43 p.m.