Triple
T8054265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Setsubun |
E187755
|
entity |
| Predicate | mamemakiMeaning |
P8493
|
FINISHED |
| Object | bean-throwing |
—
|
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: bean-throwing | Statement: [Setsubun, mamemakiMeaning, bean-throwing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mamemakiMeaning Context triple: [Setsubun, mamemakiMeaning, bean-throwing]
-
A.
typicalKanjiMeaning
Indicates that one entity is the standard or commonly accepted meaning associated with a given kanji character.
-
B.
meaningDependsOnKanji
Indicates that the meaning of something (e.g., a word or expression) is determined by, or varies according to, the specific kanji characters used.
-
C.
meaningOfPhrase
chosen
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
D.
kanji
Indicates that an entity is written in, represented by, or associated with a specific kanji character or set of kanji characters.
-
E.
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.
- 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_69ca82b15e948190a62fd7af5218426a |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f9fb8dc8190bacc1f66ddfd1cbf |
completed | March 31, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69cb049a1b9c8190811c396421ebf9c9 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:25 p.m.