The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Penn Discourse TreeBank 2.0.
Abstract
We present the second version of the Penn Discourse Treebank, PDTB-2.0, describing its lexically-grounded annotations of discourse relations and their two abstract object arguments over the 1 million word Wall Street Journal corpus. We describe all aspects of the annotation, including (a) the argument structure of discourse relations, (b) the sense annotation of the relations, and (c) the attribution of discourse relations and each of their arguments. We list the differences between PDTB-1.0 and PDTB-2.0. We present representative statistics for several aspects of the annotation in the corpus. 1.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Building a Large Annotated Corpus of English: The Penn Treebank
Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
Flagged first, then by citations
Cited by
Sorted by citations
Revisiting readability: a unified framework for predicting text quality
Pitler, E., & Nenkova, A. (2008) · Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08 · doi:10.3115/1613715.1613742 · Cited by 375
A large-scale comparison of human-written versus ChatGPT-generated essays
Herbold, S., Hautli-Janisz, A., Heuer, U., Kikteva, Z., & Trautsch, A. (2023) · Scientific Reports · doi:10.1038/s41598-023-45644-9 · Cited by 338
Human-Centric Justification of Machine Learning Predictions
Biran, O., & McKeown, K. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/202 · Cited by 84
Detecting Causal Language Use in Science Findings
Yu, B., Li, Y., & Wang, J. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1473 · Cited by 40
Towards Evaluating Narrative Quality In Student Writing
Somasundaran, S., Flor, M., Chodorow, M., Molloy, H., Gyawali, B., & McCulla, L. (2018) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00007 · Cited by 29
Metadata
- Authors
- Prasad, R., Dinesh, N., Lee, A., Miltsakaki, E., Robaldo, L., Joshi, A., & Webber, B.
- Affiliations
- University of Pennsylvania (US)
- University of Turin (IT)
- Venue
- Proceedings of the Language Resources and Evaluation Conference
- Published
- 2008-05
- Pages
- 2961-2968
- ISSN
- 2522-2686
- OpenAlex
- W2166957049
- Cited by
- 1,115
- References
- 1
- Citations by year
- 2026: 11 · 2025: 2 · 2024: 5 · 2023: 58 · 2022: 41 · 2021: 111 · 2020: 96 · 2019: 87 · 2018: 76 · 2017: 98 · 2016: 117 · 2015: 91 · 2014: 93 · 2013: 67 · 2012: 64
- FWCI
- 25.56
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Language Resources and Evaluation Conference (LREC) (publishedVersion)
- Institutional Research Information System University of Turin (University of Turin) (submittedVersion)
- Language Resources and Evaluation
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Social Sciences › Arts and Humanities › Language and Linguistics › Syntax, Semantics, Linguistic Variation
- Social Sciences › Linguistics and Language › Linguistic Studies and Language Acquisition
- Keywords
- Penn Discourse Treebank, discourse relations, argument structure, sense annotation, Wall Street Journal corpus, corpus annotation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review