Triple
T38135708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jōshū Jūshin |
E952344
|
entity |
| Predicate | hasJapaneseReadingOfName |
P143799
|
FINISHED |
| Object | Jōshū |
—
|
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: Jōshū | Statement: [Jōshū Jūshin, hasJapaneseReadingOfName, Jōshū]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJapaneseReadingOfName Context triple: [Jōshū Jūshin, hasJapaneseReadingOfName, Jōshū]
-
A.
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.
-
B.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
C.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
-
D.
hasKanjiReading
Indicates that a written kanji character is associated with a specific reading or pronunciation.
-
E.
hasJapaneseSurname
Indicates that the person or entity possesses a surname that is of Japanese origin or is commonly used in Japanese naming conventions.
- 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_69f76f09a7148190a4b91c0bacdc127a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcb089a8f881909aa9e722babd43f7 |
completed | May 7, 2026, 3:32 p.m. |
| PD | Predicate disambiguation | batch_69fc45666c5c8190913bd632ac0e5b84 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.