Elaborative Simplification as Implicit Questions Under Discussion (2023)

Abstract: Automated text simplification, a technique useful for making text more accessible to people such as children and emergent bilinguals, is often thought of as a monolingual translation task from complex sentences to simplified sentences using encoder-decoder models. This view fails to account for elaborative simplification, where new information is added into the simplified text. This paper proposes to view elaborative simplification through the lens of the Question Under Discussion (QUD) framework, providing a robust way to investigate what writers elaborate upon, how they elaborate, and how elaborations fit into the discourse context by viewing elaborations as explicit answers to implicit questions. We introduce ELABQUD, consisting of 1.3K elaborations accompanied with implicit QUDs, to study these phenomena. We show that explicitly modeling QUD (via question generation) not only provides essential understanding of elaborative simplification and how the elaborations connect with the rest of the discourse, but also substantially improves the quality of elaboration generation.

## introduction text simplification systems aim to lower the barrier of reading for a wider, more inclusive audience, for instance, children @xcite , emergent bilinguals @xcite , and individuals with language impairments @xcite . while there has been abundant research in automatic text simplification @xcite , recent data-driven efforts have focused on re-writing a sentence or passage into simpler language while preserving its meaning, often as a monolingual translation task using encoder-decoder models @xcite @xcite or editing models @xcite . simplified. those factories are gone now. new companies have come that need skilled workers with more education. new haven youth want those jobs, but they do not have the education or the skills. many do not have the money to get the training they need. that is where new haven promise comes in. it will make a difference by paying for college. new haven promise is no one-way street. ## implicit quds: what questions do elaborations answer? for a simplified document with sentences @xmath0, ..., s i-1 , s i , s i+1 , ...} where sentence i is an elaboration (i.e., @xmath1, we aim to recover the implicit question under discussion q such that e answers q. we further define the target t of the elaboration, i.e., e elaborates or explains t . the sentence that contains t is called the anchor sentence of q, and can be taken to mean that q arose from that anchor @xcite . what do ❶ read e […] 3 animal 4 it tea 5 natu of the it mea chang enemie foods o cannot ❷ formu ❹ is this ◽ yes ❸ what c elaboratio sentence why is it important for them to reach the rio grande? ❶ read elaboration (highlighted) and context 1 the giron brothers left honduras in february 2013. […] 4 it took the group 11 days to travel from honduras to the united states. 5 they traveled all the way north through mexico until they reached the rio grande river. the river divides the united states from mexico. at the border, the guide put the girons and other teens on a small raft. he paddled them across the river to texas. once they were in the united states, their guide left the teens by themselves. ❷ formulate question ❹ is this elaboration an organizational sentence? ◽ yes ☑ no ❸ what concept, and in which sentence, does the elaboration explain? sentence 5, "the rio grande river" this section presents elabqud and its annotation. elabqud contains annotated implicit quds for all 1,299 elaborations in srikanth and li (2021), along with their anchors and targets. ## question generation with the qud framework, elaborative simplification is a two-step process: this section experiments with question generation (qg) models for step (1). we explore three different settings varying how explicitly the model sees the elaboration target t and the anchor sentence, and establishing an upper bound where the model is exposed to the gold "answer" e. ## zero-shot elaboration generation finally, we experiment with the utility of questions on elaboration generation, i.e., task (2) in section 4: given c and q, generate elaboration e by modeling p (e|c, q). our hypothesis is that a good qud should be able to guide a strong language model towards generating a better elaboration than without such guidance, in the sense that the elaboration should be more on-topic, and more frequently an explanation rather than simply continuing a story. ## limitations this paper focuses on how to generate elaborations, rather than when to do so. namely, we assume that we know which sentences constitute elaborations using srikanth and li (2021)'s dataset. we leave the when question to future work, noting that sentence-level elaboration is infrequent among the articles analyzed by @xcite . at the same time, what constitutes difficult content is subjective or reader-specific. future work can explore using qud for elaborative simplification in an interactive manner. additionally, the space of possible quds given context is large, posing challenges to inquisitive-based systems for future work. another challenge with generating elaborations is inherit to elaborations themselves: because they contain information not present in the original text, they are hallucinations. it will be important to analyze the difference between helpful elaborations and undesirable hallucinations, and we leave this to future work. we also note that we focused here on english text of a particular genre (news), and that results may not generalize to other languages or other genres of text. finally, we acknowledge that the landscape of llms are rapidly changing every few months, and we have not experimented with the strongest models (i.e., gpt-4). however, the space of possible elaborations prevents unconstrained generation; the utility of qud is exactly to point to what is elaborated. as shown with our results, both question generation and elaboration generation benefit from stronger language models, hence we are optimistic about what stronger llms will bring to elaborative simplification with quds.