Triple
T994581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gigafactory Berlin-Brandenburg |
E21466
|
entity |
| Predicate | hasPlannedCapacityType |
P17734
|
FINISHED |
| Object | vehicle production per year |
—
|
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: vehicle production per year | Statement: [Gigafactory Berlin-Brandenburg, hasPlannedCapacityType, vehicle production per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedCapacityType Context triple: [Gigafactory Berlin-Brandenburg, hasPlannedCapacityType, vehicle production per year]
-
A.
hasCapacityType
Indicates that an entity possesses a specific kind or classification of capacity or capability.
-
B.
plannedCapability
chosen
Indicates that an entity is intended or scheduled to possess or provide a particular capability in the future.
-
C.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
D.
plannedUnder
Indicates that one entity has been scheduled, organized, or arranged to occur within the scope, authority, or framework of another entity.
-
E.
hasCapitalType
Indicates that a specified location’s capital is of a particular type (e.g., political, administrative, or economic capital).
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c75de88190bf7fec7a053f7a90 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2af071c819086c374a16307dfe0 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.