Sentence segmentation
17 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Sentence segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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MASC
Most implemented papers
Lexical Semantic Recognition
In lexical semantics, full-sentence segmentation and segment labeling of various phenomena are generally treated separately, despite their interdependence.
Abstractive Summarization of Spoken andWritten Instructions with BERT
nlpyang/PreSumm
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KDD Converse 2020
Summarization of speech is a difficult problem due to the spontaneity of the flow, disfluencies, and other issues that are not usually encountered in written texts.
Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks
YerevaNN/JointUD
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CONLL 2018
This paper describes our submission to CoNLL 2018 UD Shared Task.
Universal Dependency Parsing from Scratch
stanfordnlp/stanfordnlp
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CONLL 2018
This paper describes Stanford's system at the CoNLL 2018 UD Shared Task.
Fine-Grained Argument Unit Recognition and Classification
trtm/AURC
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In this work, we argue that the task should be performed on a more fine-grained level of sequence labeling.
Using Punkt for Sentence Segmentation in non-Latin Scripts: Experiments on Kurdish (Sorani) Texts
The Kurdish language is a multi-dialect, under-resourced language which is written in different scripts.
Abstractive Summarization of Spoken and Written Instructions with BERT
Summarization of speech is a difficult problem due to the spontaneity of the flow, disfluencies, and other issues that are not usually encountered in written texts.
Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translation
csebuetnlp/banglanmt
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EMNLP 2020
With the segmenter and the two methods combined, we compile a high-quality Bengali-English parallel corpus comprising of 2. 75 million sentence pairs, more than 2 million of which were not available before.
Evaluating Sentence Segmentation and Word Tokenization Systems on Estonian Web Texts
Texts obtained from web are noisy and do not necessarily follow the orthographic sentence and word boundary rules.
Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing
nlp-uoregon/trankit
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EACL 2021
Finally, we create a demo video for Trankit at: https://youtu. be/q0KGP3zGjGc.
