Data-Driven Frame-Semantic Parsing with Tree Wrapping Grammar (2023)

Abstract: We describe the first experimental results for data-driven semantic parsing with Tree Rewriting Grammars (TRGs) and semantic frames. While several theoretical papers previously discussed approaches for modeling frame semantics in the context of TRGs, this is the first data-driven implementation of such a parser. We experiment with Tree Wrapping Grammar (TWG), a grammar formalism closely related to Tree Adjoining Grammar (TAG), developed for formalizing the typologically inspired linguistic theory of Role and Reference Grammar (RRG). We use a transformer-based multi-task architecture to predict semantic supertags which are then decoded into RRG trees augmented with semantic feature structures. We present experiments for sentences in different genres for English data. We also discuss our compositional semantic analyses using TWG for several linguistic phenomena.

## introduction while many user-facing applications of natural language processing such as machine translation or sentiment analysis can these days be performed with state-of-the-art accuracy by syntax-agnostic machine learning models, grammar-based methods are still important. for one thing, they offer more transparency and insight into the decisions of a model, while in many cases having near-stateof-the-art performance @xcite @xcite . secondly, they tend to be less data-hungry and therefore more readily adapted or transferred to low-resource languages. symbolic methods for semantic parsing can also greatly contribute to grammar theory studies and to linguistic investigations of different languages. in this paper, we are interested in developing a methodology for deep semantic parsing (i.e., producing semantic representations for entire sentences) which would also allow easy transfer to different languages, including low-resource ones. we start from the typologically oriented linguistic theory of @xcite . this theory uses a common inventory of labels and structures to describe languages from different language families @xcite . the formalization of rrg using tree wrapping grammar (twg; @xcite has paved the way for using this theory in computational linguistics and for developing nlp applications such as syntactic parsers @xcite . the twg formalism is inspired by @xcite and allows for adequate modeling of longdistance dependencies. since twg is closely related to tag, we can readily apply existing computational methods developed for tag. in this work, we explore how well the methodology for compositional semantics with a tree-based syntax outlined in several theoretical papers on tag @xcite is suitable for twg and can be used for a large scale implementation. a small-scale frame-semantic parser based on the tree adjoining grammar was already implemented by @xcite . our approach differs from theirs in that it is data-driven and aims for a broad-coverage semantic parser. our method is based on transformers and contextual embeddings and we do not use a metagrammar in our application, but go for an approach based on supertagging. our work also differs from semantic role labeling (i.e., shallow semantic parsing) with tag @xcite since we are interested in deep semantic representations of the sentences. figure 1 shows how the semantic representations for the sentence john needed help can be produced compositionally with elementary trees in twg paired with frames, and figure 3 shows the frame representation for this sentence. the objective of this paper is to implement a broad-coverage semantic parser based on tree rewriting grammars. since this is the first broadcoverage implementation of a deep semantic parser for either tag or twg, we are particularly interested in modeling linguistic phenomena which we came across during this data-driven implementation. we describe this in §2. we also want to investigate if our syntax-aware methodology allows us to achieve state-of-the-art results on semantic parsing. we describe the theoretical background of our work and introduce our approach to frame-based semantics with twg in §3 and present experimental results in §4. we discuss future work in §5. ## conclusion and future work in this paper, we presented the first broad-coverage frame-semantic parser with tree wrapping grammar, a grammar formalism closely related to tree adjoining grammar. to develop our parser, we adapted the theoretical approach of @xcite to semantic parsing with tag and transferred it to twg. we explored parsing strategies for several complex linguistic constructions. we developed our transformer-based language model based on the verbatlas frame lexicon, and experimented with english data in several genres. we could see that our semantic parser shows results close to the state-of-the-art semantic parsers. in future work we want to explore the transferability of our approach to different languages, in-cluding low-resource ones. our approach to semantic parsing starts from statistical syntactic parsing for twg proposed by @xcite ; @xcite . a recent work by @xcite presents a modification of this method for crosslingual syntactic parsing based on word embeddings and english glosses. the underlying idea is to transfer supertag information from an english translation to the target sentence via word alignments. we plan to extend this method to semantics. the frame lexicon verbatlas, which we use as a frame inventory for the semantic representations, lacks relations between frames. in order to enable semantic inference and logical reasoning with our parser, we currently investigate possibilities to develop a rule-based mapping from verbatlas frames to framenet frames, which would then yield also hierarchical relations between frames.