Triple
T8300750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese Wikiquote |
E194342
|
entity |
| Predicate | hasCategorySystem |
P82601
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Japanese Wikiquote, hasCategorySystem, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCategorySystem Context triple: [Japanese Wikiquote, hasCategorySystem, true]
-
A.
usesCategorySystem
Indicates that one entity organizes or classifies things according to a particular category system defined by another entity.
-
B.
hasCategoryCount
Indicates the number of distinct categories associated with a given entity.
-
C.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
D.
hasCategoryGroup
Indicates that something is associated with, or belongs to, a broader grouping of related categories.
-
E.
hasCategoryLevel
Indicates that something is associated with a specific hierarchical category or tier within a classification system.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7e879c588190a6f95cf7795541ad |
completed | March 31, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:53 p.m.