# Yara Parser: A Fast and Accurate Dependency Parser

arXiv: https://arxiv.org/abs/1503.06733 · HTML: https://mlsanity.com/paper/1503.06733/

## Key facts

- Cited by 111 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Mar 2015.

## Built on by (most cited first, 30 of 111)

- [CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges](https://mlsanity.com/paper/2401.07339/) (2024)
- [CoAnnotating: Uncertainty-Guided Work Allocation between Human and Large Language Models for Data Annotation](https://mlsanity.com/paper/2310.15638/) (2023)
- [Agents in Software Engineering: Survey, Landscape, and Vision](https://mlsanity.com/paper/2409.09030/) (2024)
- [Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering](https://mlsanity.com/paper/2109.04014/) (2021)
- [GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models](https://mlsanity.com/paper/2406.14550/) (2024)
- [HealthFC: Verifying Health Claims with Evidence-Based Medical Fact-Checking](https://mlsanity.com/paper/2309.08503/) (2023)
- [DrDiff: Dynamic Routing Diffusion with Hierarchical Attention for Breaking the Efficiency-Quality Trade-off](https://mlsanity.com/paper/2509.02785/) (2025)
- [Foundations and Recent Trends in Multimodal Mobile Agents: A Survey](https://mlsanity.com/paper/2411.02006/) (2024)
- [Goldfish: Monolingual Language Models for 350 Languages](https://mlsanity.com/paper/2408.10441/) (2024)
- [Rehearsal-Free Modular and Compositional Continual Learning for Language Models](https://mlsanity.com/paper/2404.00790/) (2024)
- [Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation](https://mlsanity.com/paper/2407.18698/) (2024)
- [The SIGMORPHON 2022 Shared Task on Morpheme Segmentation](https://mlsanity.com/paper/2206.07615/) (2022)
- [TRUCE: Private Benchmarking to Prevent Contamination and Improve Comparative Evaluation of LLMs](https://mlsanity.com/paper/2403.00393/) (2024)
- [PresentAgent: Multimodal Agent for Presentation Video Generation](https://mlsanity.com/paper/2507.04036/) (2025)
- [Can Large Multimodal Models Uncover Deep Semantics Behind Images?](https://mlsanity.com/paper/2402.11281/) (2024)
- [A First Look at GPT Apps: Landscape and Vulnerability](https://mlsanity.com/paper/2402.15105/) (2024)
- [Parameter-Efficient Tuning Makes a Good Classification Head](https://mlsanity.com/paper/2210.16771/) (2022)
- [Bias in Opinion Summarisation from Pre-training to Adaptation: A Case Study in Political Bias](https://mlsanity.com/paper/2402.00322/) (2024)
- [LLMs in Biomedicine: A study on clinical Named Entity Recognition](https://mlsanity.com/paper/2404.07376/) (2024)
- [Afrispeech-Dialog: A Benchmark Dataset for Spontaneous English Conversations in Healthcare and Beyond](https://mlsanity.com/paper/2502.03945/) (2025)
- [Persona-judge: Personalized Alignment of Large Language Models via Token-level Self-judgment](https://mlsanity.com/paper/2504.12663/) (2025)
- [Surrogate Signals from Format and Length: Reinforcement Learning for Solving Mathematical Problems without Ground Truth Answers](https://mlsanity.com/paper/2505.19439/) (2025)
- [The Dark Side of the Language: Pre-trained Transformers in the DarkNet](https://mlsanity.com/paper/2201.05613/) (2022)
- [LinguAlchemy: Fusing Typological and Geographical Elements for Unseen Language Generalization](https://mlsanity.com/paper/2401.06034/) (2024)
- [PSSAT: A Perturbed Semantic Structure Awareness Transferring Method for Perturbation-Robust Slot Filling](https://mlsanity.com/paper/2208.11508/) (2022)
- [A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NER](https://mlsanity.com/paper/2308.14533/) (2023)
- [LARD: Large-scale Artificial Disfluency Generation](https://mlsanity.com/paper/2201.05041/) (2022)
- [Dialogue-based generation of self-driving simulation scenarios using Large Language Models](https://mlsanity.com/paper/2310.17372/) (2023)
- [Exploiting Edited Large Language Models as General Scientific Optimizers](https://mlsanity.com/paper/2503.09620/) (2025)
- [Out-of-Domain Intent Detection Considering Multi-Turn Dialogue Contexts](https://mlsanity.com/paper/2305.03237/) (2023)

## Abstract (arXiv)

Dependency parsers are among the most crucial tools in natural language processing as they have many important applications in downstream tasks such as information retrieval, machine translation and knowledge acquisition. We introduce the Yara Parser, a fast and accurate open-source dependency parser based on the arc-eager algorithm and beam search. It achieves an unlabeled accuracy of 93.32 on the standard WSJ test set which ranks it among the top dependency parsers. At its fastest, Yara can parse about 4000 sentences per second when in greedy mode (1 beam). When optimizing for accuracy (using 64 beams and Brown cluster features), Yara can parse 45 sentences per second. The parser can be trained on any syntactic dependency treebank and different options are provided in order to make it more flexible and tunable for specific tasks. It is released with the Apache version 2.0 license and can be used for both commercial and academic purposes. The parser can be found at https://github.com/yahoo/YaraParser.