Triple
T1334586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyushu dialect |
E28718
|
entity |
| Predicate | degreeOfIntelligibility |
P7448
|
FINISHED |
| Object | can be difficult for speakers of Standard Japanese to understand |
—
|
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: can be difficult for speakers of Standard Japanese to understand | Statement: [Kyushu dialect, degreeOfIntelligibility, can be difficult for speakers of Standard Japanese to understand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeOfIntelligibility Context triple: [Kyushu dialect, degreeOfIntelligibility, can be difficult for speakers of Standard Japanese to understand]
-
A.
degreeOfDecipherment
Indicates the extent to which something (such as a text, code, or script) has been successfully deciphered or made intelligible.
-
B.
intelligenceLevel
Indicates the degree or measure of cognitive ability or intelligence attributed to an entity.
-
C.
intendedReadingLevel
Indicates the reading proficiency or audience level that a text or resource is designed or meant to be understood by.
-
D.
areMutuallyIntelligibleToSomeDegree
chosen
Indicates that two or more languages or communication systems can be at least partially understood by each other’s users without prior learning or translation.
-
E.
typeOfIntelligence
Indicates that one entity is a specific kind or category of intelligence in relation to another entity.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1eb119881909dd5fbf728d9e8ba |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.