diff --git a/R/documentation-templates.R b/R/documentation-templates.R
index cd2889c2..9878d8cb 100644
--- a/R/documentation-templates.R
+++ b/R/documentation-templates.R
@@ -51,7 +51,7 @@
 #' of the data belong together and jointly form a single forecasts. This is
 #' easy e.g. for point forecast, where there is one row per forecast. For
 #' quantile or sample-based forecasts, however, there are multiple rows that
-#' belong to single forecast.
+#' belong to a single forecast.
 #'
 #' The *forecast unit* or *unit of a single forecast* is then described by the
 #' combination of columns that uniquely identify a single forecast.
diff --git a/R/forecast.R b/R/forecast.R
index f0bc738c..01256ca9 100644
--- a/R/forecast.R
+++ b/R/forecast.R
@@ -196,6 +196,7 @@ assert_forecast <- function(
 
 
 #' @importFrom cli cli_abort
+#' @rdname assert_forecast
 #' @export
 #' @keywords check-forecasts
 assert_forecast.default <- function(
@@ -211,6 +212,7 @@ assert_forecast.default <- function(
 
 
 #' @export
+#' @rdname assert_forecast
 #' @importFrom cli cli_abort
 #' @keywords check-forecasts
 assert_forecast.forecast_binary <- function(
@@ -247,6 +249,7 @@ assert_forecast.forecast_binary <- function(
 
 
 #' @export
+#' @rdname assert_forecast
 #' @importFrom cli cli_abort
 #' @keywords check-forecasts
 assert_forecast.forecast_point <- function(
diff --git a/R/metrics-quantile.R b/R/metrics-quantile.R
index d537f1d3..1a1121e1 100644
--- a/R/metrics-quantile.R
+++ b/R/metrics-quantile.R
@@ -445,7 +445,7 @@ bias_quantile <- function(observed, predicted, quantile_level, na.rm = TRUE) {
     #nolint start: keyword_quote_linter
     cli_inform(
       c(
-        "i" = "Median not available, computing bias as mean of the two
+        "i" = "Median not available, interpolating median from the two
         innermost quantiles in order to compute bias."
       )
     )
diff --git a/man/as_forecast.Rd b/man/as_forecast.Rd
index dccb753e..91a4e5e8 100644
--- a/man/as_forecast.Rd
+++ b/man/as_forecast.Rd
@@ -132,7 +132,7 @@ In order to score forecasts, \code{scoringutils} needs to know which of the rows
 of the data belong together and jointly form a single forecasts. This is
 easy e.g. for point forecast, where there is one row per forecast. For
 quantile or sample-based forecasts, however, there are multiple rows that
-belong to single forecast.
+belong to a single forecast.
 
 The \emph{forecast unit} or \emph{unit of a single forecast} is then described by the
 combination of columns that uniquely identify a single forecast.
diff --git a/man/assert_forecast.Rd b/man/assert_forecast.Rd
index 84a552a5..e2858d9e 100644
--- a/man/assert_forecast.Rd
+++ b/man/assert_forecast.Rd
@@ -2,12 +2,21 @@
 % Please edit documentation in R/forecast.R
 \name{assert_forecast}
 \alias{assert_forecast}
+\alias{assert_forecast.default}
+\alias{assert_forecast.forecast_binary}
+\alias{assert_forecast.forecast_point}
 \alias{assert_forecast.forecast_quantile}
 \alias{assert_forecast.forecast_sample}
 \title{Assert that input is a forecast object and passes validations}
 \usage{
 assert_forecast(forecast, forecast_type = NULL, verbose = TRUE, ...)
 
+\method{assert_forecast}{default}(forecast, forecast_type = NULL, verbose = TRUE, ...)
+
+\method{assert_forecast}{forecast_binary}(forecast, forecast_type = NULL, verbose = TRUE, ...)
+
+\method{assert_forecast}{forecast_point}(forecast, forecast_type = NULL, verbose = TRUE, ...)
+
 \method{assert_forecast}{forecast_quantile}(forecast, forecast_type = NULL, verbose = TRUE, ...)
 
 \method{assert_forecast}{forecast_sample}(forecast, forecast_type = NULL, verbose = TRUE, ...)
diff --git a/man/forecast_types.Rd b/man/forecast_types.Rd
index 8037f487..4c4d2648 100644
--- a/man/forecast_types.Rd
+++ b/man/forecast_types.Rd
@@ -58,7 +58,7 @@ In order to score forecasts, \code{scoringutils} needs to know which of the rows
 of the data belong together and jointly form a single forecasts. This is
 easy e.g. for point forecast, where there is one row per forecast. For
 quantile or sample-based forecasts, however, there are multiple rows that
-belong to single forecast.
+belong to a single forecast.
 
 The \emph{forecast unit} or \emph{unit of a single forecast} is then described by the
 combination of columns that uniquely identify a single forecast.
diff --git a/man/get_forecast_unit.Rd b/man/get_forecast_unit.Rd
index 60af4f64..ac1756f9 100644
--- a/man/get_forecast_unit.Rd
+++ b/man/get_forecast_unit.Rd
@@ -28,7 +28,7 @@ In order to score forecasts, \code{scoringutils} needs to know which of the rows
 of the data belong together and jointly form a single forecasts. This is
 easy e.g. for point forecast, where there is one row per forecast. For
 quantile or sample-based forecasts, however, there are multiple rows that
-belong to single forecast.
+belong to a single forecast.
 
 The \emph{forecast unit} or \emph{unit of a single forecast} is then described by the
 combination of columns that uniquely identify a single forecast.
diff --git a/man/score.Rd b/man/score.Rd
index 4f06da04..c39b6722 100644
--- a/man/score.Rd
+++ b/man/score.Rd
@@ -104,7 +104,7 @@ In order to score forecasts, \code{scoringutils} needs to know which of the rows
 of the data belong together and jointly form a single forecasts. This is
 easy e.g. for point forecast, where there is one row per forecast. For
 quantile or sample-based forecasts, however, there are multiple rows that
-belong to single forecast.
+belong to a single forecast.
 
 The \emph{forecast unit} or \emph{unit of a single forecast} is then described by the
 combination of columns that uniquely identify a single forecast.
diff --git a/tests/testthat/test-metrics-quantile.R b/tests/testthat/test-metrics-quantile.R
index 3a8eb7ae..a99ae71c 100644
--- a/tests/testthat/test-metrics-quantile.R
+++ b/tests/testthat/test-metrics-quantile.R
@@ -861,7 +861,7 @@ test_that("bias_quantile(): quantile levels must be unique", {
 test_that("bias_quantile only produces one message", {
   expect_message(
     bias_quantile(observed, predicted[, -3], quantile_level[-3]),
-    "Median not available, computing bias as mean of the two innermost quantiles in order to compute bias."
+    "Median not available, interpolating median from the two innermost quantiles in order to compute bias."
   )
 })