Triple
T30098712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matter of France |
E764934
|
entity |
| Predicate | hasBodelCategory |
P190054
|
FINISHED |
| Object | “la matière de France” |
—
|
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: “la matière de France” | Statement: [Matter of France, hasBodelCategory, “la matière de France”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodelCategory Context triple: [Matter of France, hasBodelCategory, “la matière de France”]
-
A.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
B.
hasCategories
Indicates that an entity is associated with one or more categories that classify or group it.
-
C.
hasSupportCategory
Indicates that an entity is associated with a particular type or category of support it receives or provides.
-
D.
haveCategoryCode
Indicates that an entity is associated with a specific classification or category identified by a code.
-
E.
hasCategorySystem
Indicates that an entity is associated with or organized according to a particular categorization 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_69f22474e4288190b5f895fe3974aa92 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69fcab6d41a88190a3576b4b088dcabd |
completed | May 7, 2026, 3:10 p.m. |
Created at: April 29, 2026, 7:08 p.m.