Triple
T35078671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Patent Office |
E1012372
|
entity |
| Predicate | grantsPatentType |
P2587
|
FINISHED |
| Object | European patent |
—
|
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: European patent | Statement: [European Patent Office, grantsPatentType, European patent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantsPatentType Context triple: [European Patent Office, grantsPatentType, European patent]
-
A.
typeOfPatentsGranted
chosen
Indicates the specific categories or kinds of patents that have been officially granted to an entity.
-
B.
grantedPatentAs
Indicates that a patent has been officially granted to an entity in a specified role or capacity.
-
C.
hasPatentGrant
Indicates that a patent grant exists conferring legal protection or rights to an entity for a specific invention or intellectual property.
-
D.
intellectualPropertyType
Indicates the specific category or kind of intellectual property associated with an entity (e.g., patent, copyright, trademark).
-
E.
inventionType
Indicates the specific category or kind of invention that characterizes the relationship between an invention and its type.
- 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_69f76dd32c008190853aef6028f60208 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:01 p.m.