Triple
T28950077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munich campus |
E730984
|
entity |
| Predicate | locatedInInnovationHub |
P40
|
FINISHED |
| Object | European business and innovation hub |
—
|
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 business and innovation hub | Statement: [Munich campus, locatedInInnovationHub, European business and innovation hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInInnovationHub Context triple: [Munich campus, locatedInInnovationHub, European business and innovation hub]
-
A.
hasInnovationHub
Indicates that an entity hosts, contains, or is associated with a dedicated center or facility focused on innovation activities.
-
B.
locatedInEducationalHub
Indicates that an entity is situated within a place recognized as a center or hub of educational activity or institutions.
-
C.
locatedInHubOf
Indicates that one entity is situated within the central hub or core area associated with another entity.
-
D.
locatedIn
chosen
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
E.
isNearTechnologyHub
Indicates that an entity is located close to a significant center of technological activity, such as a tech district, innovation cluster, or major tech campus.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69ffde9263248190996f970b6cf6e49d |
completed | May 10, 2026, 1:25 a.m. |
| PD | Predicate disambiguation | batch_69ffdd760f1c8190abc6c0c1cd97ba5f |
completed | May 10, 2026, 1:20 a.m. |
Created at: April 28, 2026, 8:43 a.m.