Претрага
2 items
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Development and Evaluation of Three Named Entity Recognition Systems for Serbian - The Case of Personal Names
In this paper we present a rule- and lexicon-based system for the recognition of Named Entities (NE) in Serbian news paper texts that was used to prepare a gold standard annotated with personal names. It was further used to prepare training sets for four different levels of annota tion, which were further used to train two Named Entity Recognition (NER) sys tems: Stanford and spaCy. All obtained models, together with a rule- and lexicon based system were evaluated on ...... they also show that STANFORD NER achieves the best re- call, while SPACY NER tends to have the more balanced precision and recall. Figure 3: Evaluation of SRPNER, SPACY NER and STANFORD NER on two test sets, by each named entity type 6 Online Tool for NER Serbian NER team (2019) offers an on-line ...
... 3 Stanford NER STANFORD NER (Manning et al., 2014) is a Java implementation of a Named Entity Recog- nizer by the Stanford Natural Language Process- ing group. It is also known as CRFClassifier, since 6Training NER in spaCy, https://spacy.io/usage/training#ner 7Visualization of SPACY NER for Serbian ...
... evaluation of SPACY NER, SRP- NER and STANFORD NER on STUDENTS-GOLD 5 Discussion The results of three NER systems, four models and two test texts are presented in Table 6. The re- sults show that in all cases (except one) SRPNER achieved the best precision, in all cases (except one) STANFORD NER achieved the ...Branislava Šandrih, Cvetana Krstev, Ranka Stanković. "Development and Evaluation of Three Named Entity Recognition Systems for Serbian - The Case of Personal Names" in Proceedings - Natural Language Processing in a Deep Learning World, Incoma Ltd., Shoumen, Bulgaria (2019). https://doi.org/10.26615/978-954-452-056-4_122
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Annotation of the Serbian ELTeC Collection
Ovaj rad predstavlja takozvano izdanje nivoa 2 kolekcije tekstova SrpELTeC razvijene u okviru aktivnosti Radne grupe 2 – Metode i alati COST akcije CA 16204 (Distant Reading for European Literary History) i njene specifikacije šeme. Izdanje nivoa 2 je nastavak izdanja nivoa 1, koje se koristi kao ulaz za morfosintaksičke i NER anotacije romana. Srpska obrada nivoa-2 je navedena kroz potrebne korake, uključujući metode i alate koji se koriste u tom procesu. Neki statistički podaci iz srpske kolekcije nivoa ...udaljeno čitanje, literarni korpus, tagiranje, prepoznavanje imenovanih entiteta, lematizacija, ELTeCRanka Stanković, Cvetana Krstev, Branislava Šandrih Todorović, Mihailo Škorić. "Annotation of the Serbian ELTeC Collection" in Infotheca, Faculty of Philology, University of Belgrade (2021). https://doi.org/10.18485/infotheca.2021.21.2.3