Basic Filter deletes every modiﬁed fact equestion,
r, eoriginal and replaces it with a new fact equestion,
r, enew. This would be a low recall ﬁlter as it does
not account for all possible related facts. The Strict
Filter is a high recall ﬁlter that more aggressively
removes information that may conﬂict with the
newly added fact, additionally removing all facts
that contain equestion or eoriginal. This is important
for cases such as when a question contains multiple
entities, or the linking relation is one-to-many, lead-
ing to multiple plausible answers. Together these
two settings deﬁne rough bounds on the model’s
ability to perform this task. In Table 6, we see that
FILM is able to utilize the modiﬁed KB to make
the correct prediction for 54.5% of questions in the
Basic Filter setting and 70.3% in the Strict Filter
setting.

Model
FILM
+Update Memory

Basic Filter

Strict Filter

0.0
54.5

0.0
70.3
Adaptable and Interpretable Neural Memory Over Symbolic Knowledge