Triple
T30640004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 加藤 |
E779947
|
entity |
| Predicate | alternativeKanjiForm |
P177161
|
FINISHED |
| Object | 加籐 |
—
|
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: 加籐 | Statement: [加藤, alternativeKanjiForm, 加籐]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternativeKanjiForm Context triple: [加藤, alternativeKanjiForm, 加籐]
-
A.
kanji
Indicates that an entity is written in, represented by, or associated with a specific kanji character or set of kanji characters.
-
B.
equivalentInJapaneseKanji
Indicates that one entity has the same meaning or value as another entity when written in Japanese Kanji.
-
C.
typicalKanjiSpelling
Indicates that one written form is the standard or most commonly used kanji spelling for another expression (such as a word or phrase).
-
D.
japaneseKunReading
Indicates that a Japanese kanji character has a specific native Japanese (kun) reading associated with it.
-
E.
onYomiJapanese
Indicates that the specified reading is the on’yomi (Sino-Japanese) pronunciation associated with a given kanji or term.
- 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f854486c81909396d944a55e03ab |
completed | May 3, 2026, 7:25 a.m. |
Created at: April 29, 2026, 8:29 p.m.