Automatic Extraction of Clausal Embedding Based on Large-Scale English Text Data

• URL: http://arxiv.org/abs/2506.14064v1
• Date: Mon, 16 Jun 2025 23:48:04 GMT
• Title: Automatic Extraction of Clausal Embedding Based on Large-Scale English Text Data
• Authors: Iona Carslaw, Sivan Milton, Nicolas Navarre, Ciyang Qing, Wataru Uegaki,
• Abstract summary: We present a methodological approach for detecting and annotating naturally-occurring examples of English embedded clauses.<n>Our tool has been evaluated on our dataset Golden Embedded Clause Set (GECS)<n>We present a large-scale dataset of naturally-occurring English embedded clauses which we have extracted from the open-source corpus Dolma.
• Score: 1.2582887633807602
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: For linguists, embedded clauses have been of special interest because of their intricate distribution of syntactic and semantic features. Yet, current research relies on schematically created language examples to investigate these constructions, missing out on statistical information and naturally-occurring examples that can be gained from large language corpora. Thus, we present a methodological approach for detecting and annotating naturally-occurring examples of English embedded clauses in large-scale text data using constituency parsing and a set of parsing heuristics. Our tool has been evaluated on our dataset Golden Embedded Clause Set (GECS), which includes hand-annotated examples of naturally-occurring English embedded clause sentences. Finally, we present a large-scale dataset of naturally-occurring English embedded clauses which we have extracted from the open-source corpus Dolma using our extraction tool.

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