Marcel Bollmann. 2013. POS Tagging for Historical Texts with Sparse Training Data. In Proceedings of the 7th Linguistic Annotation Workshop and Interoperability ...
How much training data is needed? → Different sizes of the training parts. Random sub-sampling n tokens for training. 1,000 ...
This paper presents a method for part-ofspeech tagging of historical data and evaluates it on texts from different corpora of historical German (15th–18th ...
Table of Contents · 4.1 Impact of punctuation · 4.2 Tagging “with handicaps” · 4.3 Tagging historical data · 4.4 Error analysis.
32 Citations · POS Tagging for Historical Texts with Sparse Training Data · Morphological and Part-of-Speech Tagging of Historical Language Data: A Comparison.
The paper discusses the challenges of POS tagging and lemmatization of historical varieties of. Italian, and reports for both tasks the results of ...
[word] In linguistics a word is the smallest element that may be uttered in isolation with semantic or pragmatic content (with literal or practical meaning).
Oct 8, 2024 · In this paper, we consider pos tagging within the framework of set-valued prediction, which allows the pos tagger to express its uncertainty via predicting a ...
Missing: Sparse | Show results with:Sparse
People also ask
What is the best model for POS tagging?
What are two POS tagging approaches?
What is POS tagging in text preprocessing?
POS tagging for historical texts with sparse training data. M Bollmann. Proceedings of the 7th Linguistic Annotation Workshop and Interoperability …, 2013. 42 ...
POS tagging for historical texts with sparse training data. Marcel Bollmann. RUB Icon. 2013. in 7th Linguistic Annotation Workshop & Interoperability with ...