Upload prompt template grounding_nli_json_alt.yaml

grounding_nli_json_alt.yaml

@@ -1,27 +1,63 @@
 prompt:
-  template: "You are a helpful and harmless AI assistant. You will be provided with a textual context and a model-generated
-    response.\nYour task is to analyze the response sentence by sentence and classify each sentence according to its relationship
-    with the provided context.\n\n**Instructions:**\n\n1. **Decompose the response into individual sentences.**\n2. **For
-    each sentence, assign one of the following labels:**\n    * **`supported`**: The sentence is entailed by the given context.\
-    \  Provide a supporting excerpt from the context.\n    * **`unsupported`**: The sentence is not entailed by the given
-    context. Provide an excerpt that is close but does not fully support the sentence.\n    * **`contradictory`**: The sentence
-    is falsified by the given context. Provide a contradicting excerpt from the context.\n    * **`no_rad`**: The sentence
-    does not require factual attribution (e.g., opinions, greetings, questions, disclaimers).  No excerpt is needed for this
-    label.\n\n3. **For each label, provide a short rationale explaining your decision.**  The rationale should be separate
-    from the excerpt.\n\n**Input Format:**\n\nThe input will consist of two parts, clearly separated:\n\n* **Context:**  The
-    textual context used to generate the response.\n* **Response:** The model-generated response to be analyzed.\n\n**Output
-    Format:**\n\nFor each sentence in the response, output a JSON object with the following fields:\n\n* `\"sentence\"`: The
-    sentence being analyzed.\n* `\"label\"`: One of `supported`, `unsupported`, `contradictory`, or `no_rad`.\n* `\"rationale\"\
-    `: A brief explanation for the assigned label.\n* `\"excerpt\"`:  A relevant excerpt from the context. Only required for
-    `supported`, `unsupported`, and `contradictory` labels.\n\nOutput each JSON object on a new line.\n\n**Example:**\n\n
-    **Input:**\n\n```\nContext: Apples are red fruits. Bananas are yellow fruits.\n\nResponse: Apples are red. Bananas are
-    green.  Enjoy your fruit!\n```\n\n**Output:**\n\n{\"sentence\": \"Apples are red.\", \"label\": \"supported\", \"rationale\"\
-    : \"The context explicitly states that apples are red.\", \"excerpt\": \"Apples are red fruits.\"}\n{\"sentence\": \"
-    Bananas are green.\", \"label\": \"contradictory\", \"rationale\": \"The context states that bananas are yellow, not green.\"\
-    , \"excerpt\": \"Bananas are yellow fruits.\"}\n{\"sentence\": \"Enjoy your fruit!\", \"label\": \"no_rad\", \"rationale\"\
-    : \"This is a general expression and does not require factual attribution.\", \"excerpt\": null}\n\n**Now, please analyze
-    the following context and response:**\n\n**User Query:**\n{{user_request}}\n\n**Context:**\n{{context_document}}\n\n**Response:**\n\
-    {{response}}"
+  template: |-
+    You are a helpful and harmless AI assistant. You will be provided with a textual context and a model-generated response.
+    Your task is to analyze the response sentence by sentence and classify each sentence according to its relationship with the provided context.
+
+    **Instructions:**
+
+    1. **Decompose the response into individual sentences.**
+    2. **For each sentence, assign one of the following labels:**
+        * **`supported`**: The sentence is entailed by the given context.  Provide a supporting excerpt from the context.
+        * **`unsupported`**: The sentence is not entailed by the given context. Provide an excerpt that is close but does not fully support the sentence.
+        * **`contradictory`**: The sentence is falsified by the given context. Provide a contradicting excerpt from the context.
+        * **`no_rad`**: The sentence does not require factual attribution (e.g., opinions, greetings, questions, disclaimers).  No excerpt is needed for this label.
+
+    3. **For each label, provide a short rationale explaining your decision.**  The rationale should be separate from the excerpt.
+
+    **Input Format:**
+
+    The input will consist of two parts, clearly separated:
+
+    * **Context:**  The textual context used to generate the response.
+    * **Response:** The model-generated response to be analyzed.
+
+    **Output Format:**
+
+    For each sentence in the response, output a JSON object with the following fields:
+
+    * `"sentence"`: The sentence being analyzed.
+    * `"label"`: One of `supported`, `unsupported`, `contradictory`, or `no_rad`.
+    * `"rationale"`: A brief explanation for the assigned label.
+    * `"excerpt"`:  A relevant excerpt from the context. Only required for `supported`, `unsupported`, and `contradictory` labels.
+
+    Output each JSON object on a new line.
+
+    **Example:**
+
+    **Input:**
+
+    ```
+    Context: Apples are red fruits. Bananas are yellow fruits.
+
+    Response: Apples are red. Bananas are green.  Enjoy your fruit!
+    ```
+
+    **Output:**
+
+    {"sentence": "Apples are red.", "label": "supported", "rationale": "The context explicitly states that apples are red.", "excerpt": "Apples are red fruits."}
+    {"sentence": "Bananas are green.", "label": "contradictory", "rationale": "The context states that bananas are yellow, not green.", "excerpt": "Bananas are yellow fruits."}
+    {"sentence": "Enjoy your fruit!", "label": "no_rad", "rationale": "This is a general expression and does not require factual attribution.", "excerpt": null}
+
+    **Now, please analyze the following context and response:**
+
+    **User Query:**
+    {{user_request}}
+
+    **Context:**
+    {{context_document}}
+
+    **Response:**
+    {{response}}
   template_variables:
     - user_request
     - context_document