Triple
T38079020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caturmahārāja |
E950799
|
entity |
| Predicate | equivalentTermInJapanese |
P57913
|
FINISHED |
| Object | Shitennō |
—
|
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: Shitennō | Statement: [Caturmahārāja, equivalentTermInJapanese, Shitennō]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentTermInJapanese Context triple: [Caturmahārāja, equivalentTermInJapanese, Shitennō]
-
A.
equivalentTitleInJapanese
chosen
Indicates that one entity has a corresponding or matching title in Japanese that is equivalent in meaning or usage to the other entity’s title.
-
B.
equivalentInJapaneseKanji
Indicates that one entity has the same meaning or value as another entity when written in Japanese Kanji.
-
C.
JapaneseTermComponent
Indicates that one element functions as a component or part of a Japanese term (such as a word, phrase, or expression).
-
D.
hasMeaningInJapanese
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Japanese language.
-
E.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
- 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:21 p.m.