It uses an SVM model. The training data is from a project called SHARPn, it is
notes from Mayo Clinic with a variety of note types and specialties represented.
As for the example, is it a real example that someone wrote "Deny hepatitis"?
That sounds more like a command than documentation of a negated concept
("denies" or "denied" would seem more common?). Even if that is a real example,
I think it's unusual enough that there are probably not examples of "Deny X" in
the training data.
Tim
-----Original Message-----
From: ouyeyu panyu
<ouy...@gmail.com<mailto:ouyeyu%20panyu%20%3couy...@gmail.com%3e>>
Reply-to: <u...@ctakes.apache.org>
To: u...@ctakes.apache.org<mailto:u...@ctakes.apache.org>,
dev@ctakes.apache.org<mailto:dev@ctakes.apache.org>
Subject: Question about negation [EXTERNAL]
Date: Wed, 16 Jan 2019 07:51:20 -0800
Hi ctakes dev team,
I have one question, hope someone can help me with it.
For negation, "Denies hepatitis” returns polarity=-1, but "Deny hepatitis”
returns polarity=1.
It is said CTAKES uses ClearTK’s PolarityCleartkAnalysisEngine for negation,
which is machine learning based.
It seems this issue is caused by the training data. Is this true? And what is
the training data and what machine learning algorithm is used? LogisticRegress,
SVM, RandomForest or something else?
Thanks.
