The link to the tool trial is: AlKhalil for Disambiguation of Arabic Text
The AlKhalil Lemmatizer is a statistical lemmatizer for Arabic that assigns a single lemma to each word in a sentence, taking into account the word context. The system comprises two modules:
- Module 1: This module performs a context-independent analysis of the word using the Alkhalil Morpho Sys 2 morphosyntactic analyzer. This module generates a list of potential lemmas for the word, based on its morphological features.
- Module 2: This module uses the context of the word to identify the correct lemma from the list of potential lemmas generated by Module 1. To do this, Module 2 uses a hidden Markov model (HMM) where the observations are the words of the sentence and the hidden states are the lemmas.
The AlKhalil Lemmatizer was trained on a labeled corpus of about 500,000 words. The lemmatizer achieved an accuracy of over 99.24% on the training set and about 94.45% on the test set.
Here are some additional details about the two modules of the AlKhalil Lemmatizer:
Module 1: Context-Independent Analysis
Module 1 uses the Alkhalil Morpho Sys 2 morphosyntactic analyzer to perform a context-independent analysis of the word. This analysis generates a list of potential lemmas for the word, based on its morphological features. For example, the word “كتاب” (book) has the following morphological features:
- Part of speech: noun
- Gender: masculine
- Number: singular
Based on these features, Module 1 would generate the following list of potential lemmas for the word “كتاب”:
- “كتاب” (book)
- “كتب” (to write)
Module 2: Context-Aware Analysis
Module 2 uses the context of the word to identify the correct lemma from the list of potential lemmas generated by Module 1. To do this, Module 2 uses a hidden Markov model (HMM). In an HMM, the observations are the words of the sentence and the hidden states are the lemmas.
The HMM works by modeling the probability of observing a sequence of words, given a sequence of lemmas. For example, the HMM might model the following probability:
P(كتاب, أنا, أقرأ) = P(كتاب, أنا, أقرأ | الكتاب) * P(الكتاب)This probability is the probability of observing the words “كتاب” (book), “أنا” (I), and “أقرأ” (I read), given that the lemma of the first word is “كتاب” (book).
Module 2 uses the HMM to calculate the probability of each potential lemma for the word, given the context of the word. The lemma with the highest probability is selected as the correct lemma.
The AlKhalil Lemmatizer is a powerful tool for improving the performance of a variety of Arabic language processing applications, such as machine translation, information retrieval, and speech recognition.