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fixtures/review.json

@@ -1,46 +1,76 @@
 {
   "spans": [
     {
-      "start": 25,
-      "end": 41,
-      "text": "Nimbus 14 laptop",
-      "label": "product",
-      "score": 0.9600220918655396,
+      "start": 155,
+      "end": 161,
+      "text": "screen",
+      "label": "feature_mention",
+      "score": 0.9743606448173523,
       "attributes": {
         "sentiment": [
           {
-            "label": "negative",
-            "score": 0.975648820400238
+            "label": "positive",
+            "score": 0.9995241165161133
           }
         ]
       }
     },
     {
-      "start": 224,
-      "end": 233,
-      "text": "Nimbus 14",
-      "label": "product",
-      "score": 0.906394898891449,
+      "start": 182,
+      "end": 190,
+      "text": "keyboard",
+      "label": "feature_mention",
+      "score": 0.9798126220703125,
       "attributes": {
         "sentiment": [
           {
-            "label": "negative",
-            "score": 0.9998642206192017
+            "label": "positive",
+            "score": 0.9994789958000183
           }
         ]
       }
     },
     {
-      "start": 408,
-      "end": 419,
-      "text": "USB-C ports",
-      "label": "product",
-      "score": 0.5385769605636597,
+      "start": 341,
+      "end": 349,
+      "text": "trackpad",
+      "label": "feature_mention",
+      "score": 0.9792487621307373,
       "attributes": {
         "sentiment": [
           {
-            "label": "negative",
-            "score": 0.8142373561859131
+            "label": "positive",
+            "score": 0.9997420907020569
+          }
+        ]
+      }
+    },
+    {
+      "start": 358,
+      "end": 363,
+      "text": "hinge",
+      "label": "feature_mention",
+      "score": 0.9491639733314514,
+      "attributes": {
+        "sentiment": [
+          {
+            "label": "positive",
+            "score": 0.9993890523910522
+          }
+        ]
+      }
+    },
+    {
+      "start": 451,
+      "end": 458,
+      "text": "Support",
+      "label": "feature_mention",
+      "score": 0.9439302682876587,
+      "attributes": {
+        "sentiment": [
+          {
+            "label": "positive",
+            "score": 0.9954706430435181
           }
         ]
       }
@@ -49,13 +79,13 @@
       "start": 510,
       "end": 525,
       "text": "docking station",
-      "label": "product",
-      "score": 0.8726967573165894,
+      "label": "feature_mention",
+      "score": 0.5191700458526611,
       "attributes": {
         "sentiment": [
           {
             "label": "negative",
-            "score": 0.9747726917266846
+            "score": 0.9989418387413025
           }
         ]
       }

model.py

@@ -53,18 +53,15 @@ DEMO = {
              'review = open("product_review.txt").read()\n'
              '\n'
              'schema = (extractor.create_schema()\n'
-             '    .entities({"product": "A product or product component mentioned in the review",\n'
-             '               "person": "A person by name or role"})\n'
+             '    .entities({"feature_mention": "A feature, component, or aspect of a product mentioned in the review"})\n'
              '    .entity_attributes({\n'
              '        "sentiment": AttributeGroup(\n'
              '            labels=["positive", "neutral", "negative"],\n'
-             '            applies_to=["product"]),\n'
-             '        "role": AttributeGroup(\n'
-             '            labels=["executive", "employee", "customer", "analyst"],\n'
-             '            applies_to=["person"])}))\n'
+             '            applies_to=["feature_mention"])}))\n'
              '\n'
              'result = extractor.extract(review, schema, include_spans=True, include_confidence=True)\n'
-             '# -> {"entities": {"product": [{"text": "docking station", "sentiment": {"label": "negative"}, ...}], ...}}'
+             '# -> {"entities": {"feature_mention": [{"text": "keyboard", "sentiment": {"label": "positive"}, ...},\n'
+             '#                            {"text": "docking station", "sentiment": {"label": "negative"}, ...}], ...}}'
          )},
     ],
 }
@@ -84,12 +81,10 @@ EXAMPLE_SCHEMAS = {
     },
     "review": {
         "entities": {
-            "product": "A product or product component mentioned in the review",
-            "person": "A person by name or role",
+            "feature_mention": "A feature, component, or aspect of a product mentioned in the review",
         },
         "attributes": {
-            "sentiment": (["positive", "neutral", "negative"], ["product"]),
-            "role": (["executive", "employee", "customer", "analyst"], ["person"]),
+            "sentiment": (["positive", "neutral", "negative"], ["feature_mention"]),
         },
     },
 }