diff --git a/gtsam/hybrid/HybridBayesNet.h b/gtsam/hybrid/HybridBayesNet.h
index fba6bb6aa..94a0762de 100644
--- a/gtsam/hybrid/HybridBayesNet.h
+++ b/gtsam/hybrid/HybridBayesNet.h
@@ -128,7 +128,7 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
    * value assignment. Note this corresponds to the Gaussian posterior p(X|M=m)
    * of the continuous variables given the discrete assignment M=m.
    *
-   * @note Any pure discrete factors are ignored.
+   * @note Be careful, as any factors not Gaussian are ignored.
    *
    * @param assignment The discrete value assignment for the discrete keys.
    * @return Gaussian posterior as a GaussianBayesNet
diff --git a/gtsam/hybrid/HybridGaussianFactorGraph.cpp b/gtsam/hybrid/HybridGaussianFactorGraph.cpp
index 0e5a34359..0c4e9c489 100644
--- a/gtsam/hybrid/HybridGaussianFactorGraph.cpp
+++ b/gtsam/hybrid/HybridGaussianFactorGraph.cpp
@@ -542,7 +542,7 @@ AlgebraicDecisionTree<Key> HybridGaussianFactorGraph::discretePosterior(
 }
 
 /* ************************************************************************ */
-GaussianFactorGraph HybridGaussianFactorGraph::operator()(
+GaussianFactorGraph HybridGaussianFactorGraph::choose(
     const DiscreteValues &assignment) const {
   GaussianFactorGraph gfg;
   for (auto &&f : *this) {
diff --git a/gtsam/hybrid/HybridGaussianFactorGraph.h b/gtsam/hybrid/HybridGaussianFactorGraph.h
index 3ef6218be..a5130ca08 100644
--- a/gtsam/hybrid/HybridGaussianFactorGraph.h
+++ b/gtsam/hybrid/HybridGaussianFactorGraph.h
@@ -230,8 +230,23 @@ class GTSAM_EXPORT HybridGaussianFactorGraph
   eliminate(const Ordering& keys) const;
   /// @}
 
-  /// Get the GaussianFactorGraph at a given discrete assignment.
-  GaussianFactorGraph operator()(const DiscreteValues& assignment) const;
+  /**
+   @brief Get the GaussianFactorGraph at a given discrete assignment. Note this
+   * corresponds to the Gaussian posterior p(X|M=m, Z=z) of the continuous
+   * variables X given the discrete assignment M=m and whatever measurements z
+   * where assumed in the creation of the factor Graph.
+   *
+   * @note Be careful, as any factors not Gaussian are ignored.
+   *
+   * @param assignment The discrete value assignment for the discrete keys.
+   * @return Gaussian factors as a GaussianFactorGraph
+   */
+  GaussianFactorGraph choose(const DiscreteValues& assignment) const;
+
+  /// Syntactic sugar for choose
+  GaussianFactorGraph operator()(const DiscreteValues& assignment) const {
+    return choose(assignment);
+  }
 };
 
 // traits