added threshold

src/__init__.py

@@ -181,8 +181,6 @@ class GBRT(Base):
         return emb/n
 
     def link(self, mentions_cands, context):
-        n_features = self.model.n_features_in_
-
         # Calculate max prior probability of all candidates.
         mentions = set([i for i, _ in mentions_cands])
         candidates = set([i for _, j in mentions_cands for i in j])
@@ -223,7 +221,7 @@ class GBRT(Base):
             X = [j + [i + 1] for i, j in enumerate(X)]
 
             # Predict
-            pred, conf = 'NIL', 0
+            pred, conf = 'NIL', 0.2
             for i in X:
                 c = self.model.predict(np.array([i[1:]]))[0]
                 if c > conf: