Triple
T2328037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naomi |
E48334
|
entity |
| Predicate | JapaneseNameOrigin |
P38935
|
FINISHED |
| Object | Japanese language (independent etymology) |
—
|
LITERAL 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: Japanese language (independent etymology) | Statement: [Naomi, JapaneseNameOrigin, Japanese language (independent etymology)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JapaneseNameOrigin Context triple: [Naomi, JapaneseNameOrigin, Japanese language (independent etymology)]
-
A.
eraNameInJapanese
Indicates the Japanese-language name used for a specific historical or calendar era.
-
B.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
C.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
D.
kun’yomiDerivedFrom
Indicates that a Japanese kun’yomi (native Japanese reading of a kanji) originates from or is historically derived from another form, source, or expression.
-
E.
hanjaName
Indicates that one entity is the Sino-Korean (hanja) written form corresponding to the name of another entity.
- F. None of above. chosen
Provenance (4 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abcc30c5e881908c5d526d7e7491d0 |
completed | March 7, 2026, 6:56 a.m. |
| PD | Predicate disambiguation | batch_69abc5926d048190a535e3f23d41de2a |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcc2fa25c8190858c1c541b914f4c |
completed | March 7, 2026, 6:56 a.m. |
Created at: March 4, 2026, 7:50 p.m.