Triple
T150069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alfred Nobel |
E3411
|
entity |
| Predicate | numberOfInventions |
P3854
|
FINISHED |
| Object | over 300 patents |
—
|
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: over 300 patents | Statement: [Alfred Nobel, numberOfInventions, over 300 patents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInventions Context triple: [Alfred Nobel, numberOfInventions, over 300 patents]
-
A.
numberOfPatents
chosen
Indicates the count of patents associated with a given entity.
-
B.
wasInventedBy
Indicates that something (typically an object, concept, or process) was created or brought into existence by a particular inventor or originator.
-
C.
typeOfPatentsGranted
Indicates the specific categories or kinds of patents that have been officially granted to an entity.
-
D.
coInventorWith
Indicates that two or more entities jointly invented or created the same invention.
-
E.
notableScientist
Indicates that the subject is a scientist who is widely recognized for significant contributions or impact in their field.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.