Triple
T38621547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uesugi Snow Lantern Festival |
E936879
|
entity |
| Predicate | languageOfSupportInformation |
P180691
|
FINISHED |
| Object | Japanese |
—
|
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: Japanese | Statement: [Uesugi Snow Lantern Festival, languageOfSupportInformation, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfSupportInformation Context triple: [Uesugi Snow Lantern Festival, languageOfSupportInformation, Japanese]
-
A.
languageOfSupportMaterials
chosen
Indicates the language in which support or help materials are provided or made available.
-
B.
secondaryLanguageSupport
Indicates that an entity provides assistance, services, or functionality in an additional (non-primary) language.
-
C.
languageOfDocumentation
Indicates the language in which the documentation for an entity is written or provided.
-
D.
usesLanguageSupport
Indicates that one entity makes use of language-related assistance, features, or services provided by another entity.
-
E.
languageSummary
Indicates a brief, high-level description or overview of a language or linguistic content.
- 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_69f76ed403208190b862dc795171353f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a022c5269888190944314074aedfe73 |
completed | May 11, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_6a02286020308190b238183f7ba2065f |
completed | May 11, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:32 p.m.