From 6063bd6df1f26743a86cc88806f417815979e22a Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Mon, 26 Jan 2026 18:43:03 +0000
Subject: [PATCH 1/2] Initial plan


From 3cda6a0859b8737f6bc6e65ab894fca05b47b8e3 Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Mon, 26 Jan 2026 18:46:19 +0000
Subject: [PATCH 2/2] Update is_uniformly_false() call sites to attribute
 access

Co-authored-by: shanest <351655+shanest@users.noreply.github.com>
---
 src/examples/indefinites/scripts/generate_expressions.py | 2 +-
 src/examples/learn_quant/scripts/generate_expressions.py | 2 +-
 src/examples/modals/scripts/generate_expressions.py      | 2 +-
 src/examples/modals/util.py                              | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/examples/indefinites/scripts/generate_expressions.py b/src/examples/indefinites/scripts/generate_expressions.py
index 8c265f41..f85ab492 100644
--- a/src/examples/indefinites/scripts/generate_expressions.py
+++ b/src/examples/indefinites/scripts/generate_expressions.py
@@ -18,7 +18,7 @@
     # filter out the trivial meaning, results in NaNs
     # iterate over keys, since we need to change the dict itself
     for meaning in list(expressions_by_meaning.keys()):
-        if meaning.is_uniformly_false():
+        if meaning.is_uniformly_false:
             del expressions_by_meaning[meaning]
 
     print(f"Generated {len(expressions_by_meaning)} unique expressions.")
diff --git a/src/examples/learn_quant/scripts/generate_expressions.py b/src/examples/learn_quant/scripts/generate_expressions.py
index 5338eb9e..2962c71f 100644
--- a/src/examples/learn_quant/scripts/generate_expressions.py
+++ b/src/examples/learn_quant/scripts/generate_expressions.py
@@ -39,7 +39,7 @@ def enumerate_quantifiers(
     # filter out the trivial meaning, results in NaNs
     # iterate over keys, since we need to change the dict itself
     for meaning in list(expressions_by_meaning.keys()):
-        if meaning.is_uniformly_false():
+        if meaning.is_uniformly_false:
             del expressions_by_meaning[meaning]
 
     return expressions_by_meaning
diff --git a/src/examples/modals/scripts/generate_expressions.py b/src/examples/modals/scripts/generate_expressions.py
index cefb629a..c6751f34 100644
--- a/src/examples/modals/scripts/generate_expressions.py
+++ b/src/examples/modals/scripts/generate_expressions.py
@@ -18,7 +18,7 @@
     # filter out the trivial meaning, results in NaNs
     # iterate over keys, since we need to change the dict itself
     for meaning in list(expressions_by_meaning.keys()):
-        if meaning.is_uniformly_false():
+        if meaning.is_uniformly_false:
             del expressions_by_meaning[meaning]
 
     print(f"Generated {len(expressions_by_meaning)} unique expressions.")
diff --git a/src/examples/modals/util.py b/src/examples/modals/util.py
index 1caa1cd6..4dec8729 100644
--- a/src/examples/modals/util.py
+++ b/src/examples/modals/util.py
@@ -158,7 +158,7 @@ def dataframe_to_language(
         )
 
         if (
-            meaning.is_uniformly_false()
+            meaning.is_uniformly_false
         ):  # often there will be no usable referents due to can_express being False, above
             continue
         # search for a matching recorded meaning