Triple
T7572879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freiburg im Breisgau |
E179286
|
entity |
| Predicate | hasGreenPolicy |
P53738
|
FINISHED |
| Object | emphasis on renewable energy |
—
|
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: emphasis on renewable energy | Statement: [Freiburg im Breisgau, hasGreenPolicy, emphasis on renewable energy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenPolicy Context triple: [Freiburg im Breisgau, hasGreenPolicy, emphasis on renewable energy]
-
A.
hasEnvironmentalPolicy
chosen
Indicates that an entity has established, adopted, or follows a formal policy or set of guidelines related to environmental practices or impacts.
-
B.
hasGreenSpaces
Indicates that an entity includes or is associated with areas of vegetation or natural greenery, such as parks, gardens, or lawns.
-
C.
greenProtection
Indicates that an entity provides or is subject to protection related to environmental or ecological preservation.
-
D.
hasPolicyGoal
Indicates that an entity is associated with, or aims to achieve, a specific policy objective or target.
-
E.
hasVillageGreen
Indicates that one entity possesses or includes a village green as part of its area or facilities.
- 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_69c69f316e50819081a271c85c06f918 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f94710a0819094508356b8d610ab |
completed | March 27, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69c6f4de77048190b8769e717fdcf8e7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:51 p.m.