Triple
T7572865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freiburg im Breisgau |
E179286
|
entity |
| Predicate | VaubanKnownFor |
P77538
|
FINISHED |
| Object | sustainable urban district |
—
|
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: sustainable urban district | Statement: [Freiburg im Breisgau, VaubanKnownFor, sustainable urban district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: VaubanKnownFor Context triple: [Freiburg im Breisgau, VaubanKnownFor, sustainable urban district]
-
A.
hasBuildingNamedAfterHim
Indicates that a person has a building that is named in their honor.
-
B.
builtMonument
Indicates that one entity constructed or created a monument in honor of, or related to, another entity.
-
C.
architectOfCommissionedBuilding
Indicates that a person served as the architect responsible for designing a building that was specifically commissioned.
-
D.
inscriptionFamousFor
Indicates that an inscription is widely recognized or notable specifically because of the referenced feature, event, content, or characteristic.
-
E.
baroqueArchitect
Indicates that one entity is an architect who works in, is associated with, or is characterized by the Baroque architectural style in relation to another entity.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69c6f5b1a6a08190b9ff2bc8a7befe0d |
completed | March 27, 2026, 9:25 p.m. |
Created at: March 27, 2026, 3:51 p.m.