diff --git a/interface/TextMiningService.py b/interface/TextMiningService.py
index 39760df204309a4c7e7c5e0c85209803d36979f9..b22f8acf753b79c94dfb64efcbd0cce0bfc908f0 100644
--- a/interface/TextMiningService.py
+++ b/interface/TextMiningService.py
@@ -1,6 +1,7 @@
 from abc import ABCMeta, abstractmethod
 from typing import List
 
+
 class Publication():
     def __init__(self, pmc_id, pm_id, doi, preprint_id, other_id):
         self.pmc_id = pmc_id
@@ -11,15 +12,23 @@ class Publication():
 
 
 class TextMiningService(metaclass=ABCMeta):
-    
+
     def __init__(self, name: str, description: str):
         self.name = name
         self.description = description
-    
+
     @abstractmethod
-    def getMentions(self, entities: List) -> List[Publication]:
-        """
-        Mentions at publication level
+    def getMentions(self, entities: List[str], limit: int = 20) -> List[Publication]:
+        """Returs a list of publications for a given list of entity IDs in which the entities appear.
+
+        Arguments:
+            entities {List[str]} -- [description]
+
+        Keyword Arguments:
+            limit {int} -- [description] (default: {20})
+
+        Returns:
+            List[Publication] -- [description]
         """
         pass
 
@@ -31,4 +40,3 @@ class TextMiningService(metaclass=ABCMeta):
         To-do: decide how to handle resources that can provide co-occurrences at sentence level
         """
         pass
-