Triple
T16846051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kai |
E409540
|
entity |
| Predicate | hasMeaningInJapanese |
P125083
|
FINISHED |
| Object | ocean |
—
|
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: ocean | Statement: [Kai, hasMeaningInJapanese, ocean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningInJapanese Context triple: [Kai, hasMeaningInJapanese, ocean]
-
A.
possibleKanjiMeaning
Indicates that a given meaning is a possible or candidate interpretation associated with a particular 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.
typicalKanjiMeaning
Indicates that one entity is the standard or commonly accepted meaning associated with a given kanji character.
-
D.
hasMeaningInSanskrit
Indicates that one entity (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Sanskrit language.
-
E.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b3541a008190b2a97cfea92b170f |
completed | April 18, 2026, 4:37 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:24 a.m.