Triple
T31279571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kōji |
E797622
|
entity |
| Predicate | typicalKanaSpelling |
P143799
|
FINISHED |
| Object | こうじ |
—
|
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: こうじ | Statement: [Kōji, typicalKanaSpelling, こうじ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalKanaSpelling Context triple: [Kōji, typicalKanaSpelling, こうじ]
-
A.
typicalKanjiSpelling
Indicates that one written form is the standard or most commonly used kanji spelling for another expression (such as a word or phrase).
-
B.
onYomiJapanese
Indicates that the specified reading is the on’yomi (Sino-Japanese) pronunciation associated with a given kanji or term.
-
C.
japaneseKunReading
Indicates that a Japanese kanji character has a specific native Japanese (kun) reading associated with it.
-
D.
JapaneseNameReading
chosen
Indicates that one entity is the reading or pronunciation (e.g., in kana or romaji) of a Japanese name represented by the other entity.
-
E.
usesKatakanaFor
Indicates that one entity is written or represented using katakana script in relation to another entity.
- 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_69f224def9088190a37034eab3daf57f |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 9:13 p.m.