diff --git a/pipeline/utils.py b/pipeline/utils.py
index 944a351..e7a7065 100644
--- a/pipeline/utils.py
+++ b/pipeline/utils.py
@@ -222,19 +222,18 @@ class Feature():
     Instance variables:
 
     interval -- Interval: time of feature in the media file
-    source -- the source of the feature (ie feature extractor) (default: "unknown")
-    path -- the path to the media file
+    source -- the original Source of the media (a Source object)
+    feature_extractor -- the feature extractor that created this Feature (default: "unknown")
     score -- the score of the feature (eg laughter confidence score, [0, 1] = { x ∈ ℝ | 0 ≤ x ≤ 1 }) (default: 0.0)
 
     Notes:
 
     - score is notionally in the closed interval [0, 1], but this is not enforced -- it is up to the feature extractor to ensure this (or use scores outside this range if desired -- eg a feature manually selected by user input might have a score of 2.0 so it is sorted 'above' other features)
-    - sorts based on interval, then source, then score
-    - path should never be unknown, since we need it to make clips from
+    - sorts based on interval, then feature_extractor, then score
+    - source should never be unknown, since we need it to make clips from
     """
-    # TODO: consider renaming score to something more generic
 
-    def __init__(self, interval=None, source=None, score=None, path=None):
+    def __init__(self, interval=None, source: Source|None=None, feature_extractor=None, score=None):
         """Create a feature with an interval, source, and score
 
         Expects a ready-made interval; source and score are optional
@@ -243,14 +242,14 @@ class Feature():
             raise ValueError("Interval must be provided")
         self.interval = interval
 
-        if path is None:
-            raise ValueError("Path must be provided")
-        self.path = path
-
         if source is None:
-            source = "unknown"
+            raise ValueError("A Source must be provided")
         self.source = source
 
+        if feature_extractor is None:
+            feature_extractor = "unknown"
+        self.feature_extractor = feature_extractor
+
         if score is None:
             score = 0.0
         self.score = score
@@ -259,23 +258,26 @@ class Feature():
     # which delegate to the Interval class :)
 
     @classmethod
-    def from_start(cls, start=None, source=None, score=None, path=None):
-        return cls(interval=Interval.from_start(start), source=source, score=score, path=path)
+    def from_start(cls, start=None, source=None, feature_extractor=None, score=None):
+        return cls(interval=Interval.from_start(start), source=source,
+                   feature_extractor=feature_extractor, score=score)
 
     @classmethod
-    def from_end(cls, end=None, source=None, score=None, path=None):
-        return cls(interval=Interval.from_end(end), source=source, score=score, path=path)
+    def from_end(cls, end=None, source=None, feature_extractor=None, score=None):
+        return cls(interval=Interval.from_end(end), source=source,\
+                   feature_extractor=feature_extractor, score=score)
 
     def __repr__(self):
         return f"Feature({self.interval}, {self.source}, {self.score})"
 
     def __lt__(self, other):
-        """Sort based on interval, then source, then score"""
+        """Sort based on interval, then feature_extractor, then score"""
         if self.interval == other.interval:
-            if self.source == other.source:
+            if self.feature_extractor == other.feature_extractor:
                 return self.score < other.score
-            return self.source < other.source
+            return self.feature_extractor < other.feature_extractor
         return self.interval < other.interval
+
     def to_json(self):
         """Return a dict representation of the feature for JSON encoding