Triple
T32423456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noma Prize for Translation of Japanese Literature |
E828515
|
entity |
| Predicate | notableLanguageOfTranslation |
P52478
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Noma Prize for Translation of Japanese Literature, notableLanguageOfTranslation, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageOfTranslation Context triple: [Noma Prize for Translation of Japanese Literature, notableLanguageOfTranslation, English]
-
A.
languageOfTranslatedWorks
Indicates the language into which works have been translated.
-
B.
notableEnglishTranslator
Indicates that one entity is a notable translator who has translated works into English or is recognized for English translation.
-
C.
alsoTranslatedAs
Indicates that something has an alternative translation or rendering in another language or form.
-
D.
notableLanguageOfWorks
Indicates that a particular language is especially prominent or significant among the works created by an entity.
-
E.
languageOfTranslations
chosen
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
- 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_69f3491b28bc8190b75cea7a507f337b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:54 a.m.