Triple
T4251084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isidore |
E95852
|
entity |
| Predicate | hasUsageCategory |
P15481
|
FINISHED |
| Object | Christian given name |
—
|
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: Christian given name | Statement: [Isidore, hasUsageCategory, Christian given name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUsageCategory Context triple: [Isidore, hasUsageCategory, Christian given name]
-
A.
hasPassengerUsageCategory
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
B.
hasCategoryOn
chosen
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
C.
hasUsageNote
Indicates that there is an associated explanatory note describing how or when something should be used.
-
D.
hasSpecialCategory
Indicates that an entity is associated with a designated special or exceptional category distinct from its standard classifications.
-
E.
hasSeparateSupportingCategory
Indicates that an entity is associated with an additional, distinct category used specifically for supporting or auxiliary classification purposes separate from its primary category.
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ea059108190aa00f0f20673e0ac |
completed | March 12, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.