The Effect of Context on Metaphor Paraphrase Aptness Judgments
This addresses a specific problem in natural language processing for metaphor understanding, but it is incremental as it builds on existing work with a focused experimental approach.
The study investigated how document context influences metaphor paraphrase aptness judgments, finding that adding context compresses scores toward the center of the scale, raising low and decreasing high out-of-context ratings.
We conduct two experiments to study the effect of context on metaphor paraphrase aptness judgments. The first is an AMT crowd source task in which speakers rank metaphor paraphrase candidate sentence pairs in short document contexts for paraphrase aptness. In the second we train a composite DNN to predict these human judgments, first in binary classifier mode, and then as gradient ratings. We found that for both mean human judgments and our DNN's predictions, adding document context compresses the aptness scores towards the center of the scale, raising low out of context ratings and decreasing high out of context scores. We offer a provisional explanation for this compression effect.