Penn-Helsinki Parsed Corpus of Early Modern English: First Parsing Results and Analysis
Not on the map. Why?
Abstract (arXiv)
We present the first parsing results on the Penn-Helsinki Parsed Corpus of Early Modern English (PPCEME), a 1.9 million word treebank that is an important resource for research in syntactic change. We describe key features of PPCEME that make it challenging for parsing, including a larger and more varied set of function tags than in the Penn Treebank. We present results for this corpus using a modified version of the Berkeley Neural Parser and the approach to function tag recovery of Gabbard et al (2006). Despite its simplicity, this approach works surprisingly well, suggesting it is possible to recover the original structure with sufficient accuracy to support linguistic applications (e.g., searching for syntactic structures of interest). However, for a subset of function tags (e.g., the tag indicating direct speech), additional work is needed, and we discuss some further limits of this approach. The resulting parser will be used to parse Early English Books Online, a 1.1 billion word corpus whose utility for the study of syntactic change will be greatly increased with the addition of accurate parse trees.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 13 of its 50 references that are in the map. First posted on arXiv 15 Dec 2021.
Builds on
13 of 50 references.
References · 13
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2018Deep contextualized word representationscited by 2,290
- 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,947
- 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
- 2015Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Bookscited by 1,043
- 2019FinBERT: Financial Sentiment Analysis with Pre-trained Language Modelscited by 385
- 2018Constituency Parsing with a Self-Attentive Encodercited by 199
- 2018Multilingual Constituency Parsing with Self-Attention and Pre-Trainingcited by 117
- 2020LEGAL-BERT: The Muppets straight out of Law Schoolcited by 111
- 2017A Minimal Span-Based Neural Constituency Parsercited by 59
- 2019Probing Biomedical Embeddings from Language Modelscited by 39
1 more
- 2016Part-of-Speech Tagging for Historical Englishcited by 3
Built on by
Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
2 papers.