Surface structure and interpretation

By Mark Steedman. 1996

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Citations in the corpus

Grammar-Based Grounded Lexicon Learning (2022, background): “In contrast, G2L2 is a neuro-symbolic model that integrates the combinatory categorial grammar formalism [36] with joint perceptual learning and concept learning, to directly learn meanings from images and texts.”
Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars (2005, methodology): “The grammar formalism we use is combinatory categorial grammar (CCG) (Steedman, 1996, 2000).”
Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions (2013, methodology): “This approach is closely related to Steedman’s generalized Skolem terms (2011).2”
Scaling Semantic Parsers with On-the-Fly Ontology Matching (2013, methodology): “Use the CCG combinators to combine lexical categories to give the full underpecified logical form l0.”
Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World (2013, methodology): “The first step performs a beam search over CCG parses, producing k possible logical forms `1, ..., `k.”
Learning Context-Dependent Mappings from Sentences to Logical Form (2009, methodology): “Finally, the CCG (Steedman, 1996; Steedman, 2000) parsing setup is closely related to previous CCG research, including work on learning parsing models (Clark and Curran, 2003), wide-coverage semantic parsing (Bos et al., 2004) and grammar induction (Watkinson and Manandhar, 1999).”
Online Learning of Relaxed CCG Grammars for Parsing to Logical Form (2007, background): “Combinatory categorial grammar (CCG) is a syntactic theory that models a wide range of linguistic phenomena (Steedman, 1996; Steedman, 2000).”
Scalable Semantic Parsing with Partial Ontologies (2015, methodology): “On the apposition dataset, 65% of errors stems from parsing, either in apposition detection or CCG parsing.”
An Activation-Based Model of Sentence Processing as Skilled Memory Retrieval (2005, methodology): “The passing down of gap features (Gazdar, 1981; Gazdar, Klein, Pullum, & Sag, 1985) is similar to the use of the SLASH feature in Headdriven Phrase-structure Grammar (Pollard & Sag, 1994), and the vocabulary of gapped categories is inspired by (Combinatorial) Categorial Grammar (Bar-Hillel, 1953; S”
Practical Semantic Parsing for Spoken Language Understanding (2019, background): “…the semantic parsing literature: semantic role schemes (Palmer et al., 2005; Meyers et al., 2004; Baker et al., 1998), syntax/semantics interfaces (Steedman, 1996), executable logical forms (Liang, 2013; Kate et al., 2005), and general purpose meaning representations (Banarescu et al., 2013;…”
Bootstrapping Semantic Parsers from Conversations (2011, methodology): “Each intermediate node in the tree is constructed with one of a small set of CCG combinator rules, see the explanation from Steedman (1996; 2000).”
Periphrasis as collocation (2015, background): “In contrast, I assume with many syntacticians that syntactic systems are best described in phrase-structural terms, as incrementally built combinations of signs (see among many others Harman 1963; Bresnan 1978; Gazdar et al. 1985; Pollard and Sag 1987; Steedman 1996).”
Word learning and the acquisition of syntactic-semantic overhypotheses (2018, unknown): “The incremental learner implements the formalism of combinatory categorial grammar (CCG; Steedman, 1996).”
Weakly Supervised Training of Semantic Parsers (2012, methodology): “We demonstrate our approach by training a Combinatory Categorial Grammar (CCG) (Steedman, 1996) that parses sentences into logical forms containing any of 77 relations from Freebase.”
A Natural Proof System for Natural Language (2017, methodology): “…of derivations over fixed lexical categories increases exponentially with the number of lexical elements.4 For more details about the CCG formalism and its linguistic and computational applications, we recommended to consult (Steedman, 1996), (Steedman, 2000), or Steedman and Baldridge (2011).”