Triple
T36706750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lac operon model |
E906380
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | genetic regulatory model |
C62102
|
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: genetic regulatory model Context triple: [lac operon model, instanceOf, genetic regulatory model]
-
A.
qualitative rule in gene regulatory network theory
A qualitative rule in gene regulatory network theory is a logical, often discrete, relationship that specifies how the activity state of one or more genes or regulatory elements determines the activation, repression, or maintenance of another gene’s expression without relying on precise quantitative parameters.
-
B.
gene regulatory protein
A gene regulatory protein is a molecule, typically a transcription factor, that binds specific DNA sequences or associated factors to control the timing, location, and level of gene expression.
-
C.
regulatory system
A regulatory system is a coordinated set of mechanisms, rules, and processes designed to monitor, control, and adjust the behavior of a system to maintain stability, compliance, or desired performance.
-
D.
systems biology research center
A systems biology research center is an interdisciplinary institution that integrates experimental biology, computational modeling, and high-throughput data analysis to understand complex biological systems as interacting networks rather than isolated components.
-
E.
model in complex systems
chosen
A model in complex systems is a simplified, often computational or mathematical representation of interacting components whose collective behavior exhibits emergent, nonlinear, and adaptive dynamics that cannot be easily inferred from the properties of individual parts.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:12 p.m.