A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends

As more and more Arabic texts emerged on the Internet, extracting important information from these Arabic texts is especially useful. As a fundamental technology, Named entity recognition (NER) serves as the core component in information extraction technology, while also playing a critical role in many other Natural Language Processing (NLP) systems, such as question answering and knowledge graph building. In this paper, we provide a comprehensive review of the development of Arabic NER, especially the recent advances in deep learning and pre-trained language model. Specifically, we first introduce the background of Arabic NER, including the characteristics of Arabic and existing resources for Arabic NER. Then, we systematically review the development of Arabic NER methods. Traditional Arabic NER systems focus on feature engineering and designing domain-specific rules. In recent years, deep learning methods achieve significant progress by representing texts via continuous vector representations. With the growth of pre-trained language model, Arabic NER yields better performance. Finally, we conclude the method gap between Arabic NER and NER methods from other languages, which helps outline future directions for Arabic NER.Comment: Accepted by IEEE TKD

The Mass-Metallicity Relation of Dwarf Galaxies at the Cosmic Noon in the JWST Era

We present the mass-metallicity relation (MZR) at $z=2-3$ in the stellar mass range of $M_\star\approx 10^{6.5}-10^{9.5}M_\odot$ using 55 dwarf galaxies in the Abell 2744 and SMACS J0723-3732 galaxy cluster fields. These dwarf galaxies are identified and confirmed by deep JWST/NIRISS imaging and slitless grism spectroscopic observations. Taking advantage of the gravitational lensing effect, we extend the previous MZR relation at $z=2-3$ to a much lower mass regime by more than 2.5 orders of magnitude compared with previous studies. We find that the MZR has a shallower slope at the low-mass end ($M_\star<10^{9}M_\odot$) compared to that at the high-mass end ($M_\star>10^{9}M_\odot$), with a slope turnover point at around the stellar mass of $10^9 M_\odot$. This implies that dominating feedback processes in dwarf galaxies may be different from that in galaxies with higher mass. From $z=3$ to $z=2$, the metallicity of the dwarf galaxies is enhanced by $\approx0.1$ dex for a given stellar mass, consistent with the mild evolution found in galaxies with higher mass. Further, we confirm the existence of a 3D relation between the gas-phase metallicity, stellar mass, and star formation rate, i.e., fundamental metallicity relation (FMR), in dwarf galaxies at $z=2-3$. Our derived FMR, which has no significant redshift evolution, can be used as a benchmark to understand the origin of the anti-correlation between SFR and metallicity of dwarf galaxies in the high-redshift Universe.Comment: 16 pages, 4 figures, 1 table, submitted to AAS Journal; welcome comment

Adjacent-Track InSAR Processing for Large-Scale Land Subsidence Monitoring in the Hebei Plain

Large-scale land subsidence has threatened the safety of the Hebei Plain in China. For tens of thousands of square kilometers of the Hebei Plain, large-scale subsidence monitoring is still one of the most difficult problems to be solved. In this paper, we employed the small baseline subset (SBAS) and NSBAS technique to monitor the land subsidence in the Hebei Plain (45,000 km2). The 166 Sentinel-1A data of adjacent-track 40 and 142 collected from May 2017 to May 2019 were used to generate the average deformation velocity and deformation time-series. A novel data fusion flow for the generation of land subsidence velocity of adjacent-track is presented and tested, named as the fusion of time-series interferometric synthetic aperture radar (TS-InSAR) results of adjacent-track using synthetic aperture radar amplitude images (FTASA). A cross-comparison analysis between the two tracks results and two TS-InSAR results was carried out. In addition, the deformation results were validated by leveling measurements and benchmarks on bedrock results, reaching a precision 9 mm/year. Twenty-six typical subsidence bowls were identified in Handan, Xingtai, Shijiazhuang, Hengshui, Cangzhou, and Baoding. An average annual subsidence velocity over −79 mm/year was observed in Gaoyang County of Baoding City. Through the cause analysis of the typical subsidence bowls, the results showed that the shallow and deep groundwater funnels, three different land use types over the building construction, industrial area, and dense residential area, and faults had high spatial correlation related to land subsidence bowls