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

arXiv: https://arxiv.org/abs/2506.14064 · HTML: https://mlsanity.com/paper/2506.14064/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 26 references that are in the map.
- First posted on arXiv 16 Jun 2025.

## Builds on (most cited first, 4 of 4)

- [Constituency Parsing with a Self-Attentive Encoder](https://mlsanity.com/paper/1805.01052/) (2018)
- [Multilingual Constituency Parsing with Self-Attention and Pre-Training](https://mlsanity.com/paper/1812.11760/) (2018)
- [Syntactic Search by Example](https://mlsanity.com/paper/2006.03010/) (2020)
- [Frequency, Acceptability, and Selection: A case study of clause-embedding](https://mlsanity.com/paper/2004.04106/) (2020)

## Built on by (most cited first, 1 of 1)

- [What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies](https://mlsanity.com/paper/2603.02082/) (2026)

## Abstract (arXiv)

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.