From 467028db2937e59ae62442bf5398711c98cd6227 Mon Sep 17 00:00:00 2001
From: Adrien Ball <adrien.ball@snips.ai>
Date: Mon, 6 May 2019 17:16:41 +0200
Subject: [PATCH] Accept ambiguous results from DeterministicIntentParser when
 confidence score is above 0.5 (#797)

---
 CHANGELOG.md                                  |  1 +
 .../deterministic_intent_parser.py            |  2 +-
 .../tests/test_deterministic_intent_parser.py | 46 ++++++++++++++++---
 3 files changed, 42 insertions(+), 7 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 87bcacd23..ad50985f1 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -4,6 +4,7 @@ All notable changes to this project will be documented in this file.
 ## [Unreleased]
 ### Changed
 - Re-score ambiguous `DeterministicIntentParser` results based on slots [#791](https://github.com/snipsco/snips-nlu/pull/791)
+- Accept ambiguous results from `DeterministicIntentParser` when confidence score is above 0.5 [#797](https://github.com/snipsco/snips-nlu/pull/797)
 
 ## [0.19.6]
 ### Fixed
diff --git a/snips_nlu/intent_parser/deterministic_intent_parser.py b/snips_nlu/intent_parser/deterministic_intent_parser.py
index d683cb708..496c49ea1 100644
--- a/snips_nlu/intent_parser/deterministic_intent_parser.py
+++ b/snips_nlu/intent_parser/deterministic_intent_parser.py
@@ -203,7 +203,7 @@ def parse(self, text, intents=None, top_n=None):
             if top_intents:
                 intent = top_intents[0][RES_INTENT]
                 slots = top_intents[0][RES_SLOTS]
-                if intent[RES_PROBA] < 1.0:
+                if intent[RES_PROBA] <= 0.5:
                     # return None in case of ambiguity
                     return empty_result(text, probability=1.0)
                 return parsing_result(text, intent, slots)
diff --git a/snips_nlu/tests/test_deterministic_intent_parser.py b/snips_nlu/tests/test_deterministic_intent_parser.py
index fff82927b..a01305eb0 100644
--- a/snips_nlu/tests/test_deterministic_intent_parser.py
+++ b/snips_nlu/tests/test_deterministic_intent_parser.py
@@ -17,7 +17,7 @@
 from snips_nlu.pipeline.configs import DeterministicIntentParserConfig
 from snips_nlu.result import (
     extraction_result, intent_classification_result, unresolved_slot,
-    empty_result)
+    empty_result, parsing_result)
 from snips_nlu.tests.utils import FixtureTest, TEST_PATH
 
 
@@ -244,7 +244,7 @@ def test_should_parse_intent_with_duplicated_slot_names(self):
         self.assertDictEqual(expected_intent, parsing[RES_INTENT])
         self.assertListEqual(expected_slots, parsing[RES_SLOTS])
 
-    def test_should_ignore_ambiguous_utterances(self):
+    def test_should_ignore_completely_ambiguous_utterances(self):
         # Given
         dataset_stream = io.StringIO("""
 ---
@@ -268,23 +268,30 @@ def test_should_ignore_ambiguous_utterances(self):
         # Then
         self.assertEqual(empty_result(text, 1.0), res)
 
-    def test_should_ignore_subtly_ambiguous_utterances(self):
+    def test_should_ignore_very_ambiguous_utterances(self):
         # Given
         dataset_stream = io.StringIO("""
 ---
 type: intent
 name: intent_1
 utterances:
-  - meeting tomorrow
+  - "[event_type](meeting) tomorrow"
 
 ---
 type: intent
 name: intent_2
 utterances:
-  - meeting [time:snips/datetime](today)""")
+  - call [time:snips/datetime](today)
+
+---
+type: entity
+name: event_type
+values:
+  - call
+  - diner""")
         dataset = Dataset.from_yaml_files("en", [dataset_stream]).json
         parser = DeterministicIntentParser().fit(dataset)
-        text = "meeting tomorrow"
+        text = "call tomorrow"
 
         # When
         res = parser.parse(text)
@@ -292,6 +299,33 @@ def test_should_ignore_subtly_ambiguous_utterances(self):
         # Then
         self.assertEqual(empty_result(text, 1.0), res)
 
+    def test_should_parse_slightly_ambiguous_utterances(self):
+        # Given
+        dataset_stream = io.StringIO("""
+---
+type: intent
+name: intent_1
+utterances:
+  - call tomorrow
+
+---
+type: intent
+name: intent_2
+utterances:
+  - call [time:snips/datetime](today)""")
+        dataset = Dataset.from_yaml_files("en", [dataset_stream]).json
+        parser = DeterministicIntentParser().fit(dataset)
+        text = "call tomorrow"
+
+        # When
+        res = parser.parse(text)
+
+        # Then
+        expected_intent = intent_classification_result(
+            intent_name="intent_1", probability=2. / 3.)
+        expected_result = parsing_result(text, expected_intent, [])
+        self.assertEqual(expected_result, res)
+
     def test_should_not_parse_when_not_fitted(self):
         # Given
         parser = DeterministicIntentParser()