Triple
T5151443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LAB University of Applied Sciences |
E116202
|
entity |
| Predicate | hasFieldCluster |
P10152
|
FINISHED |
| Object | Business and hospitality management |
—
|
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: Business and hospitality management | Statement: [LAB University of Applied Sciences, hasFieldCluster, Business and hospitality management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFieldCluster Context triple: [LAB University of Applied Sciences, hasFieldCluster, Business and hospitality management]
-
A.
hasPrimaryClusterIn
Indicates that an entity’s main or most significant cluster is located within or associated with a specified cluster or grouping.
-
B.
hasFieldName
Indicates that one entity is associated with, or identified by, a specific field name in a data structure or schema.
-
C.
hasOpenCluster
Indicates that an entity possesses or is associated with an open star cluster.
-
D.
hasITCluster
Indicates that an entity possesses, hosts, or is associated with a specific information technology (IT) cluster.
-
E.
hasFieldDivision
chosen
Indicates that one entity is organizationally divided into, or associated with, a specific field-based subdivision of another entity.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c1354c81908176703b4853c1a4 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b0fbb88190851e2d7ae1bdcc09 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:44 p.m.