Triple
T35687608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kashiwa-no-ha Smart City development |
E1031192
|
entity |
| Predicate | hasEnglishInformation |
P194681
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kashiwa-no-ha Smart City development, hasEnglishInformation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishInformation Context triple: [Kashiwa-no-ha Smart City development, hasEnglishInformation, yes]
-
A.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
B.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
C.
hasEnglishComponent
Indicates that something includes or is associated with a component that is in the English language.
-
D.
hasEnglishReception
Indicates that something has been received, interpreted, or responded to within an English-speaking context.
-
E.
hasEnglishGloss
Indicates that one entity serves as the English-language gloss or explanatory translation for the other entity.
- F. None of above. chosen
Provenance (4 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_69f76e0bb6608190ad3a1880be54a17d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
| PDg | Predicate description generation | batch_69fd7fd9be2881908a7f00e0e8822de8 |
completed | May 8, 2026, 6:16 a.m. |
Created at: May 3, 2026, 4:05 p.m.