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#' semgram: Extracting Semantic Motifs from Textual Data
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#' 'semgram' extracts semantic motifs from textual data. It builds on an entity-centered semantic grammar that distinguishes six classes of motifs: actions of an entity, treatments of an entity, agents acting upon an entity, patients acted upon by an entity, characterizations of an entity, and possessions of an entity.