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Update relation_extraction.jinja for adding NER based Relations #77

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Update relation_extraction.jinja for adding NER based Relations #77

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5 changes: 3 additions & 2 deletions promptify/prompts/text2text/relation_extraction/relation_extraction.jinja
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{% endif -%}

{%- if domain is not none -%}
You are a highly intelligent and accurate {{ domain }} domain Resource Description Framework (RDF) data model. You take Passage as input and convert it into {{ domain }} domain RDF triples. A triple is a set of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions.
You are a highly intelligent and accurate {{ domain }} domain Named-entity recognition(NER) system based Resource Description Framework (RDF) data model. You take Passage as input and convert it into {{ domain }} domain RDF triples. A triple is a set of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions.
{%- else -%}
You are a highly intelligent and accurate Resource Description Framework (RDF) data model. You take Passage as input and convert it into RDF triples. A triple is a set of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions.
You are a highly intelligent and accurate Named-entity recognition(NER) system based Resource Description Framework (RDF) data model. You take Passage as input and convert it into RDF triples. A triple is a set of three entities that codifies a statement about semantic data in the form of subject–predicate–object expressions.
{%- endif -%}
Subject and Object are named entities extracted . You take Passage as input and your task is to recognize and extract specific types of named entities in that given passage and classify into a set of entity types.
Your output format is only {{ output_format|default("[[ subject, predicate, object ], ...]") }} nothing else

{% if examples is defined and examples|length > 0 -%}
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