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Concurrent hidden structure & grammar learning
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In: Proceedings of the Society for Computation in Linguistics (2022)
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42 |
Can language models capture syntactic associations without surface cues? A case study of reflexive anaphor licensing in English control constructions
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In: Proceedings of the Society for Computation in Linguistics (2022)
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43 |
Universal Dependencies and Semantics for English and Hebrew Child-directed Speech
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In: Proceedings of the Society for Computation in Linguistics (2022)
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44 |
Learning Input Strictly Local Functions: Comparing Approaches with Catalan Adjectives
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In: Proceedings of the Society for Computation in Linguistics (2022)
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45 |
Learning Constraints on Wh-Dependencies by Learning How to Efficiently Represent Wh-Dependencies: A Developmental Modeling Investigation With Fragment Grammars
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In: Proceedings of the Society for Computation in Linguistics (2022)
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46 |
Typological Implications of Tier-Based Strictly Local Movement
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In: Proceedings of the Society for Computation in Linguistics (2022)
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47 |
Parsing Early Modern English for Linguistic Search
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In: Proceedings of the Society for Computation in Linguistics (2022)
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Abstract:
This work addresses the question of whether the output of a state-of-the-art parser is accurate enough to support research in theoretical linguistics. In order to build reliable models of syntactic change, we aim to eventually parse the 1.5-billion-word Early English Books Online (EEBO) corpus. But since EEBO is not yet parsed, we begin by constructing and testing a parser on the 1.7-million-word Penn-Helsinki Parsed Corpus of Early Modern English (PPCEME). In order to obtain robust results, we define an 8-fold split on PPCEME. We then evaluate the parser with evalb and, more relevantly for us, with a task-specific metric - namely, its accuracy in parsing 6 sentence types necessary to track the rise of auxiliary do (as in They did not come vs. its historical precursor They came not). Retrieving the relevant sentences from the gold and test versions with CorpusSearch queries, we find that the parser's accuracy promises to be sufficient for our purposes. A remaining concern is the variability of the output, which we plan to address with three pieces of future work sketched in the conclusion.
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Keyword:
Computational Linguistics; historical linguistics; parsing; syntax
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URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1246&context=scil https://scholarworks.umass.edu/scil/vol5/iss1/13
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48 |
When Classifying Arguments, BERT Doesn't Care About Word Order. Except When It Matters
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In: Proceedings of the Society for Computation in Linguistics (2022)
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49 |
Remodelling complement coercion interpretation
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In: Proceedings of the Society for Computation in Linguistics (2022)
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50 |
Inferring Inferences: Relational Propositions for Argument Mining
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In: Proceedings of the Society for Computation in Linguistics (2022)
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51 |
ANLIzing the Adversarial Natural Language Inference Dataset
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In: Proceedings of the Society for Computation in Linguistics (2022)
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52 |
Analysis of Language Change in Collaborative Instruction Following
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In: Proceedings of the Society for Computation in Linguistics (2022)
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53 |
SCiL 2022 Editors' Note
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In: Proceedings of the Society for Computation in Linguistics (2022)
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Sociolinguistically-aware computational models of Mandarin-English codeswitching
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In: Proceedings of the Linguistic Society of America; Vol 7, No 1 (2022): Proceedings of the Linguistic Society of America; 5247 ; 2473-8689 (2022)
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57 |
ASCNET - The popularity of Asclepius in times of plagues ...
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Assessing neural network understanding of perspectival motion verbs ...
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