Revisiting Syntax-Based Approach in Negation Scope Resolution (2023)

Abstract: Negation scope resolution is the process of detecting the negated part of a sentence. Unlike the syntax-based approach employed in previous research, state-of-the-art methods performed better without the explicit use of syntactic structure. This work revisits the syntax-based approach and re-evaluates the effectiveness of syntactic structure in negation scope resolution. We replace the parser utilized in the prior works with state-of-the-art parsers and modify the syntax-based heuristic rules. The experimental results demonstrate that the simple modifications enhance the performance of the prior syntax-based method to the same level as state-of-the-art end-to-end neural-based methods.

## introduction negation is a common linguistic phenomenon that frequently appears in natural language. consequently, its detection is crucial for various nlp applications, including sentiment analysis, relation extraction and medical data mining. typically, the negation detection task is broken down into two subtasks: (i) detecting negation cues (words, affixes, or phrases that express negations) and (ii) resolving their scopes (parts of a sentence affected by the negation cue). in example (1) below, the word "not" is the negation cue (marked in bold) and word sequences "he did" and "go to school" form the scope (underlined parts). motivated by the point mentioned above, this work revisits the syntax-based approach for negation scope resolution. we use state-of-the-art parsers to re-evaluate the earlier syntax-based approach. we also modify the syntactic-based heuristic rules used in the prior syntax-based method. our experimental results demonstrate that the prior method, based on heuristics for syntax structure, can obtain the same level of performance as stateof-the-art methods based on end-to-end neural networks. ## related work this section describes the syntax-based method proposed by @xcite , based on which we re-evaluate the usefulness of syntax for negation scope resolution. their approach assumes that the scope of negation corresponds to a constituent. as an example, let us consider the sentence (2). in the first step, the sentence is parsed and all the constituents that dominate the negation cue are considered as scope candidates. for example, in sentence (2), six constituents highlighted in figure 1 are selected as candidates. in the second step, one constituent is selected from the candidates using heuristics or a classifier. we describe the heuristic method, which we use in this work. this method selects one constituent from the candidates using scope resolution heuristics shown in figure 2 . the 14 rules that form the heuristics are applied in order from top to bottom; the rules are listed in a specific-to-general order. each rule is represented as a path pattern and some rules have additional constraints (if part). for example, the fifth rule "dt//sbar if sbar\whadvp" will be activated and the constituent sbar is selected when the negation cue is a determiner (dt), provided that it has an ancestor sbar if the sbar has a child whadvp. if no rule is activated, it uses a default scope, which expands the scope to the left and the right of the negation cue until either a sentence boundary or a punctuation is found. the alignment of the constituent and the scope is not always straightforward. sentence (1) is one of such illustration. in this sentence, the scope of the negation cue "not" does not cross the coordination boundary: the coordinating conjunction "and", its following conjunct "stayed home" and the punctuation "." are not included in the scope. to deal with such a case, @xcite adopted some heuristics to remove certain elements from the constituent in the following way: for sentence (1), the scope "he did, go to school" is correctly resolved using the series of process. the constituent s is selected as the scope of the cue according to the first and second steps. in the third step, the coordinating conjunction "and", and its conjunct "stayed home" are removed by the first heuristic rule for discontinuous scope, and the punctuation "." is removed by the above first heuristic rule (removed parts are enclosed in figure 3 ). ## revisiting the syntax-based method in this section, we revise the method described in the previous section to re-evaluate the syntax-based approach in negation scope resolution. section 3.1 describes the parsers we use in this work. sections 3.2 and 3.3 discuss the modifications we made for the second and the third steps of @xcite 's method, respectively. ## experiment to re-evaluate the syntax-based approach to negation scope resolution, we conducted an experiment 2 . this section describes the detail of the experiment. we explain the dataset, settings and results in sections 4.1, 4.2 and 4.3, respectively. ## conclusion this work re-evaluated the syntax-based approach in negation scope resolution. we replaced the parser used in the prior works with the state-ofthe-art parsers. we also slightly modified the syntax-based heuristic rules designed in the prior work. the experimental results demonstrate that the prior syntax-based approach can obtain high performance comparable to those of state-of-theart methods. this work gives a strong baseline for the negation scope resolution task and opens up the possibility of accurate and interpretable negation scope resolution. in future work, we will introduce a tree-based neural model into the constituent selection process to enhance the performance of the scope prediction. it would also be interesting to apply the syntaxbased approach to the scope resolution of other linguistic phenomena, for example, speculation or quantifier.