Triple
T7778353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Wikipedia |
E221449
|
entity |
| Predicate | usesCategorySystem |
P78944
|
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: [French Wikipedia, usesCategorySystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCategorySystem Context triple: [French Wikipedia, usesCategorySystem, yes]
-
A.
containsCategory
Indicates that one entity includes or encompasses a specific category as part of its classification or organizational structure.
-
B.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
C.
hasCategoryWithin
Indicates that one category is contained within or is a subcategory of another category.
-
D.
hasSupportCategory
Indicates that an entity is associated with a particular type or category of support it receives or provides.
-
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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
| PDg | Predicate description generation | batch_69cae7e47c5c8190bca90d45b3cdc25e |
completed | March 30, 2026, 9:15 p.m. |
Created at: March 30, 2026, 4:16 p.m.