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app.py

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+# # NER
+
+# Notebook implementation of named entity recognition.
+# Adapted from [promptify](https://github.com/promptslab/Promptify/blob/main/promptify/prompts/nlp/templates/ner.jinja).
+
+import json
+
+import minichain
+
+# Prompt to extract NER tags as json
+
+class NERPrompt(minichain.TemplatePrompt):
+    template_file = "ner.pmpt.tpl"
+
+    def parse(self, response, inp):
+        return json.loads(response)
+
+# Use NER to ask a simple queston.
+
+class TeamPrompt(minichain.Prompt):
+    def prompt(self, inp):
+        return "Can you describe these basketball teams? " + \
+            " ".join([i["E"] for i in inp if i["T"] =="Team"])
+
+    def parse(self, response, inp):
+        return response
+
+# Run the system.
+
+with minichain.start_chain("ner") as backend:
+    p1 = NERPrompt(backend.OpenAI())
+    p2 = TeamPrompt(backend.OpenAI())
+    prompt = p1.chain(p2)
+    results = prompt(
+        {"text_input": "An NBA playoff pairing a year ago, the 76ers (39-20) meet the Miami Heat (32-29) for the first time this season on Monday night at home.",
+         "labels" : ["Team", "Date"],
+         "domain": "Sports"
+         }
+    )
+    print(results)
+
+# View prompt examples.
+
+# + tags=["hide_inp"]
+NERPrompt().show(
+    {
+        "input": "I went to New York",
+        "domain": "Travel",
+        "labels": ["City"]
+    },
+    '[{"T": "City", "E": "New York"}]',
+)
+# -
+
+# View log.
+
+minichain.show_log("ner.log")

ner.pmpt.tpl

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+You are a highly intelligent and accurate {{ domain }} domain Named-entity recognition(NER) system. You take Passage as input and your task is to recognize and extract specific types of {{ domain }} domain named entities in that given passage and classify into a set of following predefined entity types:
+
+{% for l in labels %}
+* {{ l }}
+{% endfor %}
+
+Your output format is only {{ output_format|default('[{"T": type of entity from predefined entity types, "E": entity in the input text}]') }} form, no other form.
+
+Input: {{ text_input }}
+Output:

requirements.txt

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+gradio
+git+https://github.com/srush/minichain
+manifest-ml