## 6 Results and Analysis  
Table 6 shows the accuracy scores obtained on our proposed test dataset. A total of 8590 words were processed to evaluate the Urdu lemmatizer. The proposed algorithm  
\begin{table}
\begin{tabular}{c l l l} \hline \hline
**Source** & **Articles** & \begin{tabular}{l} **Words** \\ **per** \\ **Article** \\ \end{tabular} & \
\begin{tabular}{l} **Total** \\ **Words** \\ \end{tabular} \\ \hline \multirow{2}{*}{Tweets} & News tweets & 1500 & \multirow{2}{*}{2000} \\  & Election tweets & 500 & \\ \hline \multirow{4}{*}{Counter Corpus} & 2 Documents from sports domain & 330 & \multirow{4}{*}{2042} \\  & 2 Documents from showbiz domain & 339 & \\ \cline{1-1}  & 2 documents from foreign domain & 405 & \\ \cline{1-1}  & 5 Documents from business domain & 600 & \\ \cline{1-1}  & 2 documents from National domain & 368 & \\ \hline Wikipedia dump & 2 documents from Wikipedia dump & 2409 & 2409 \\ \hline \multirow{4}{*}{Blogs} & Social media & 340 & \multirow{4}{*}{2139} \\  & Motivation & 437 & \\ \cline{1-1}  & Importance of Urdu Blogs & 348 & \\ \cline{1-1}  & Importance of Dua & 132 & \\ \cline{1-1}  & Pakistan & 349 & \\ \cline{1-1}  & Corona Virus & 533 & \\ \hline \hline \end{tabular}
\begin{tabular}{c l l l} \hline \hline
**Corpus** & **Total Number** & **Total Number of** & **Total Numbers of Same** & **IAA** \\  & **of Words** & **Conflicted Words** & **Annotated Words** & \\ \hline Test & 8590 & 763 & 7827 & 7827/8590 \\ Dataset & & & & \\ \hline IAA & & & 0.91 = 91\% \\ \hline \hline \end{tabular}
\end{table}
Table 4: Source details of the test dataset.  
\begin{table}
\begin{tabular}{c l l l} \hline \hline
**Corpus** & **Total Number** & **Total Number of** & **Total Numbers of Same** & **IAA** \\  & **of Words** & **Conflicted Words** & **Annotated Words** & \\ \hline Test & 8590 & 763 & 7827 & 7827/8590 \\ Dataset & & & & \\ \hline IAA & & & 0.91 = 91\% \\ \hline \hline \end{tabular}
\end{table}
Table 5: Detailed statistics of IAA for the test dataset.  
was analyzed on two different variations: (1) with-PoS-DLA (dictionary look-up approach with part of speech tag) refers to an input method wherein words are given to the Urdu lemmatizer with their respective part of speech tags, and, by using the dictionary look-up approach, it returns the lemma of a word, Table 6; (2) without-PoS-DLA (dictionary look-up approach without part of speech tag) refers to an input method in which only words are given to the Urdu lemmatizer. The most frequent PoS tag is assigned to the word using a developed PoS tagger by algorithm and, finally, it will return the lemma of a word using a dictionary look-up approach.  
The best result (accuracy = 76.44%) was obtained by using the without-PoS-DLA approach. The reason for this best performance was that the USAS PoS tagger [24] assigned the most suitable and frequently used input tag. Using the with-PoS-DLA approach, we achieved accuracy = 66.79%. A possible reason for the poorer performance is that the tagset was assigned by humans (native users, not domain experts). Urdu is rich in morphology, so it is challenging to create a complete dictionary with lemmas of all words used in the Urdu language. A detailed description is provided in Section 6.1.