Update README.md

README.md

@@ -7,4 +7,78 @@ language:
 pretty_name: SrpKor4Tagging training dataset
 size_categories:
 - 100K<n<1M
----
+---
+
+
+Corpus is created via mix of literary (⅓) and administrative (⅔) texts in Serbian.
+It is tagged for POS for 2 tagsets: Universal POS tagset and SrpLemKor tagset (made according to traditional, descriptive Serbian grammar) and lemmatized
+
+
+It is constituted of a single jsonl file that can be loaded via:
+
+```python
+from datasets import load_dataset
+dataset = load_dataset("jerteh/SrpKor4Tagging")
+```
+
+Preview:
+
+```python
+ds = dataset["train"][1389]
+for x, y, z in zip(ds["token"], ds["ud"], ds["lemma"]):
+    print(x, y, z)
+
+Okrugle ADJ okrugao
+mongolske ADJ mongolski
+fizionomije NOUN fizionomija
+behu AUX biti
+ustupile VERB ustupiti
+mesto NOUN mesto
+licima NOUN lice
+evropskijeg ADJ evropski
+tipa NOUN tip
+, PUNCT ,
+prljavim ADJ prljav
+, PUNCT ,
+obradatelim ADJ obradateo
+i CCONJ i
+iscrpenim ADJ iscrpen
+. PUNCT .
+```
+
+Citation:
+
+```bibtex
+@inproceedings{stankovic-etal-2020-machine,
+    title = "Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for {S}erbian",
+    author = "Stankovic, Ranka  and
+      {\v{S}}andrih, Branislava  and
+      Krstev, Cvetana  and
+      Utvi{\'c}, Milo{\v{s}}  and
+      Skoric, Mihailo",
+    editor = "Calzolari, Nicoletta  and
+      B{\'e}chet, Fr{\'e}d{\'e}ric  and
+      Blache, Philippe  and
+      Choukri, Khalid  and
+      Cieri, Christopher  and
+      Declerck, Thierry  and
+      Goggi, Sara  and
+      Isahara, Hitoshi  and
+      Maegaard, Bente  and
+      Mariani, Joseph  and
+      Mazo, H{\'e}l{\`e}ne  and
+      Moreno, Asuncion  and
+      Odijk, Jan  and
+      Piperidis, Stelios",
+    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
+    month = may,
+    year = "2020",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2020.lrec-1.487",
+    pages = "3954--3962",
+    abstract = "The training of new tagger models for Serbian is primarily motivated by the enhancement of the existing tagset with the grammatical category of a gender. The harmonization of resources that were manually annotated within different projects over a long period of time was an important task, enabled by the development of tools that support partial automation. The supporting tools take into account different taggers and tagsets. This paper focuses on TreeTagger and spaCy taggers, and the annotation schema alignment between Serbian morphological dictionaries, MULTEXT-East and Universal Part-of-Speech tagset. The trained models will be used to publish the new version of the Corpus of Contemporary Serbian as well as the Serbian literary corpus. The performance of developed taggers were compared and the impact of training set size was investigated, which resulted in around 98{\%} PoS-tagging precision per token for both new models. The sr{\_}basic annotated dataset will also be published.",
+    language = "English",
+    ISBN = "979-10-95546-34-4",
+}
+```