To Drop or Not to Drop? Predicting Argument Ellipsis Judgments: A Case
  Study in Japanese
Yukiko Ishizuki Tatsuki Kuribayashi Yuichiroh Matsubayashi Ryohei Sasano Kentaro Inui
Speakers sometimes omit certain arguments of a predicate in a sentence; such
omission is especially frequent in pro-drop languages. This study addresses a
question about ellipsis -- what can explain the native speakers' ellipsis
decisions? -- motivated by the interest in human discourse processing and
writing assistance for this choice. To this end, we first collect large-scale
human annotations of whether and why a particular argument should be omitted
across over 2,000 data points in the balanced corpus of Japanese, a
prototypical pro-drop language. The data indicate that native speakers overall
share common criteria for such judgments and further clarify their quantitative
characteristics, e.g., the distribution of related linguistic factors in the
balanced corpus. Furthermore, the performance of the language model-based
argument ellipsis judgment model is examined, and the gap between the systems'
prediction and human judgments in specific linguistic aspects is revealed. We
hope our fundamental resource encourages further studies on natural human
ellipsis judgment.