Triple
T21692872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centre for Statistics and Data Science |
E535414
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | data science research unit |
C30442
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: data science research unit Context triple: [Centre for Statistics and Data Science, instanceOf, data science research unit]
-
A.
data science institute
chosen
A data science institute is an organization dedicated to advancing the theory and practice of data-driven analysis through education, research, and collaboration across disciplines.
-
B.
machine learning research institute
A machine learning research institute is an organization dedicated to advancing the theory, algorithms, and applications of machine learning through systematic research, experimentation, and collaboration.
-
C.
computer science research center
A computer science research center is an institution dedicated to advancing knowledge and innovation in computing through focused research, collaboration, and dissemination of results across areas such as algorithms, systems, artificial intelligence, and human-computer interaction.
-
D.
multidisciplinary research unit
A multidisciplinary research unit is an organized group that integrates expertise, methods, and perspectives from multiple academic or professional fields to collaboratively investigate complex problems and generate comprehensive insights.
-
E.
data scientist
A data scientist is a professional who uses statistical analysis, programming, and domain knowledge to extract insights and build predictive models from complex data.
- F. None of above.
Provenance (1 batch)
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_69e0c46a6ee481908836e1420fb78c9b |
completed | April 16, 2026, 11:13 a.m. |
Created at: April 16, 2026, 6:45 p.m.