Triple
T3607600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hokkaido dialect of Japanese |
E76409
|
entity |
| Predicate | phonologicalInfluenceFrom |
P40496
|
FINISHED |
| Object | Tohoku dialects |
—
|
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: Tohoku dialects | Statement: [Hokkaido dialect of Japanese, phonologicalInfluenceFrom, Tohoku dialects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: phonologicalInfluenceFrom Context triple: [Hokkaido dialect of Japanese, phonologicalInfluenceFrom, Tohoku dialects]
-
A.
hasLexicalInfluenceOn
Indicates that one linguistic element (such as a word, phrase, or lexicon) has affected or shaped the form, usage, or meaning of another linguistic element.
-
B.
hasPhonologicalBasisFor
chosen
Indicates that one entity serves as the phonological source, motivation, or foundation for another entity.
-
C.
languageInfluence
Indicates that one language has an effect on the development, usage, or characteristics of another language.
-
D.
hasPhonologicalSimilarityTo
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
E.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
- 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc228e24481909ae6a1e4ad796917 |
completed | March 8, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69adb83d8b1c8190b3bddbc5dc995a87 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.