Triple
T13955215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kasukabe Depot |
E335637
|
entity |
| Predicate | languageUsedOnSite |
P16555
|
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: [Kasukabe Depot, languageUsedOnSite, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedOnSite Context triple: [Kasukabe Depot, languageUsedOnSite, Japanese]
-
A.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
B.
languageOfOfficialWebsite
chosen
Indicates the language in which an entity’s official website is primarily written or presented.
-
C.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
D.
languageOfCode
Indicates that a programming code artifact is written in, or uses, a particular programming language.
-
E.
projectLanguageCode
Indicates the programming or markup language used in a project, represented by its standardized language code.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e78a4a481908e438745631a43c0 |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.