Marginal contribution of a text document
From an NLP perspective, the main issue is to identify and extract the terms/relations of interest from the text.
It may be easy if the sentences always appear like these simple examples: one can use pattern matching &quot;the &lt;entity&gt; is &lt;property1&gt; [and &lt;property2&gt;]&quot; (no need for ML).
However with general text it's a quite complex problem which would probably require training an ad-hoc model from annotated data. This would generally involve the tasks of Named Entity Recognition and Relation Extraction.